{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "1dbecff9",
   "metadata": {},
   "source": [
    "# <center><font face=\"楷体\" color=\"orange\">天津大学——马梓航</font></center>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "3b24f250",
   "metadata": {},
   "outputs": [],
   "source": [
    "#导包\n",
    "\n",
    "import pyarrow.parquet as pq\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "import statsmodels.api as sm\n",
    "from patsy import dmatrices\n",
    "from scipy.stats import spearmanr, ttest_1samp\n",
    "import matplotlib.pyplot as plt\n",
    "from tqdm import tqdm\n",
    "import warnings\n",
    "import cvxpy as cp"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "83a298e2",
   "metadata": {},
   "outputs": [],
   "source": [
    "#不显示警告\n",
    "\n",
    "warnings.filterwarnings(\"ignore\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "d9aa1935",
   "metadata": {},
   "outputs": [],
   "source": [
    "#plt预设置参数\n",
    "\n",
    "#plt设置参数\n",
    "plt.rcParams[\"font.size\"]=16\n",
    "plt.rcParams[\"font.sans-serif\"]=[\"SimHei\"]\n",
    "plt.rcParams['axes.unicode_minus'] = False"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1c613b29",
   "metadata": {},
   "source": [
    "## **一、读取数据**"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "47778c73",
   "metadata": {},
   "source": [
    "> dailydata"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "3ab9a2a6",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th>AVERAGE_PRICE</th>\n",
       "      <th>DY-ADJ_AF-CLOSE_PRICE_2</th>\n",
       "      <th>DY-ADJ_AF-HIGHEST_PRICE_2</th>\n",
       "      <th>DY-ADJ_AF-LOWEST_PRICE_2</th>\n",
       "      <th>DY-ADJ_AF-OPEN_PRICE_2</th>\n",
       "      <th>DY-ADJ_AF-TURNOVER_VOL</th>\n",
       "      <th>DY-BASIC-DEAL_AMOUNT</th>\n",
       "      <th>DY-BASIC-MARKET_VALUE</th>\n",
       "      <th>DY-BASIC-NEG_MARKET_VALUE</th>\n",
       "      <th>DY-BASIC-TURNOVER_RATE</th>\n",
       "      <th>DY-BASIC-TURNOVER_VALUE</th>\n",
       "      <th>DY-IND-CHG_STATUS</th>\n",
       "      <th>DY-IND-DEAL_VALUE</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>DATE</th>\n",
       "      <th>CODE</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
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       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th rowspan=\"5\" valign=\"top\">2010-01-04</th>\n",
       "      <th>000001</th>\n",
       "      <td>989.634107</td>\n",
       "      <td>978.291</td>\n",
       "      <td>1014.188</td>\n",
       "      <td>977.053</td>\n",
       "      <td>1011.712</td>\n",
       "      <td>806410</td>\n",
       "      <td>20836.0</td>\n",
       "      <td>7.362983e+10</td>\n",
       "      <td>6.933075e+10</td>\n",
       "      <td>0.0083</td>\n",
       "      <td>5.802495e+08</td>\n",
       "      <td>4</td>\n",
       "      <td>27848.41</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>000002</th>\n",
       "      <td>1080.801182</td>\n",
       "      <td>1074.195</td>\n",
       "      <td>1101.557</td>\n",
       "      <td>1074.195</td>\n",
       "      <td>1099.530</td>\n",
       "      <td>1749491</td>\n",
       "      <td>68592.0</td>\n",
       "      <td>1.165492e+11</td>\n",
       "      <td>1.023546e+11</td>\n",
       "      <td>0.0100</td>\n",
       "      <td>1.034345e+09</td>\n",
       "      <td>4</td>\n",
       "      <td>15079.67</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>000004</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>68.339</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>8.397668e+08</td>\n",
       "      <td>7.030741e+08</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>-1</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>000005</th>\n",
       "      <td>58.661610</td>\n",
       "      <td>58.858</td>\n",
       "      <td>59.448</td>\n",
       "      <td>58.072</td>\n",
       "      <td>59.055</td>\n",
       "      <td>3444239</td>\n",
       "      <td>12059.0</td>\n",
       "      <td>5.476858e+09</td>\n",
       "      <td>5.473321e+09</td>\n",
       "      <td>0.0245</td>\n",
       "      <td>1.334784e+08</td>\n",
       "      <td>4</td>\n",
       "      <td>11068.78</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>000006</th>\n",
       "      <td>224.459023</td>\n",
       "      <td>222.885</td>\n",
       "      <td>227.495</td>\n",
       "      <td>222.685</td>\n",
       "      <td>227.094</td>\n",
       "      <td>482074</td>\n",
       "      <td>4417.0</td>\n",
       "      <td>5.639878e+09</td>\n",
       "      <td>5.485748e+09</td>\n",
       "      <td>0.0128</td>\n",
       "      <td>7.054856e+07</td>\n",
       "      <td>4</td>\n",
       "      <td>15972.05</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                   AVERAGE_PRICE  DY-ADJ_AF-CLOSE_PRICE_2  \\\n",
       "DATE       CODE                                             \n",
       "2010-01-04 000001     989.634107                  978.291   \n",
       "           000002    1080.801182                 1074.195   \n",
       "           000004       0.000000                   68.339   \n",
       "           000005      58.661610                   58.858   \n",
       "           000006     224.459023                  222.885   \n",
       "\n",
       "                   DY-ADJ_AF-HIGHEST_PRICE_2  DY-ADJ_AF-LOWEST_PRICE_2  \\\n",
       "DATE       CODE                                                          \n",
       "2010-01-04 000001                   1014.188                   977.053   \n",
       "           000002                   1101.557                  1074.195   \n",
       "           000004                      0.000                     0.000   \n",
       "           000005                     59.448                    58.072   \n",
       "           000006                    227.495                   222.685   \n",
       "\n",
       "                   DY-ADJ_AF-OPEN_PRICE_2  DY-ADJ_AF-TURNOVER_VOL  \\\n",
       "DATE       CODE                                                     \n",
       "2010-01-04 000001                1011.712                  806410   \n",
       "           000002                1099.530                 1749491   \n",
       "           000004                   0.000                       0   \n",
       "           000005                  59.055                 3444239   \n",
       "           000006                 227.094                  482074   \n",
       "\n",
       "                   DY-BASIC-DEAL_AMOUNT  DY-BASIC-MARKET_VALUE  \\\n",
       "DATE       CODE                                                  \n",
       "2010-01-04 000001               20836.0           7.362983e+10   \n",
       "           000002               68592.0           1.165492e+11   \n",
       "           000004                   0.0           8.397668e+08   \n",
       "           000005               12059.0           5.476858e+09   \n",
       "           000006                4417.0           5.639878e+09   \n",
       "\n",
       "                   DY-BASIC-NEG_MARKET_VALUE  DY-BASIC-TURNOVER_RATE  \\\n",
       "DATE       CODE                                                        \n",
       "2010-01-04 000001               6.933075e+10                  0.0083   \n",
       "           000002               1.023546e+11                  0.0100   \n",
       "           000004               7.030741e+08                  0.0000   \n",
       "           000005               5.473321e+09                  0.0245   \n",
       "           000006               5.485748e+09                  0.0128   \n",
       "\n",
       "                   DY-BASIC-TURNOVER_VALUE  DY-IND-CHG_STATUS  \\\n",
       "DATE       CODE                                                 \n",
       "2010-01-04 000001             5.802495e+08                  4   \n",
       "           000002             1.034345e+09                  4   \n",
       "           000004             0.000000e+00                 -1   \n",
       "           000005             1.334784e+08                  4   \n",
       "           000006             7.054856e+07                  4   \n",
       "\n",
       "                   DY-IND-DEAL_VALUE  \n",
       "DATE       CODE                       \n",
       "2010-01-04 000001           27848.41  \n",
       "           000002           15079.67  \n",
       "           000004                NaN  \n",
       "           000005           11068.78  \n",
       "           000006           15972.05  "
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "parquet_file = pq.ParquetFile(r'basic_data\\daily_data.parquet')\n",
    "data = parquet_file.read().to_pandas()\n",
    "data.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "9c971f9d",
   "metadata": {},
   "outputs": [
    {
     "data": {
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      "text/plain": [
       "                       open      high       low     close            市值\n",
       "DATE       CODE                                                        \n",
       "2010-01-04 000001   978.291  1014.188   977.053  1011.712  7.362983e+10\n",
       "           000002  1074.195  1101.557  1074.195  1099.530  1.165492e+11\n",
       "           000004    68.339     0.000     0.000     0.000  8.397668e+08\n",
       "           000005    58.858    59.448    58.072    59.055  5.476858e+09\n",
       "           000006   222.885   227.495   222.685   227.094  5.639878e+09"
      ]
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     "execution_count": 9,
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   "source": [
    "data=data[['DY-ADJ_AF-CLOSE_PRICE_2','DY-ADJ_AF-HIGHEST_PRICE_2','DY-ADJ_AF-LOWEST_PRICE_2','DY-ADJ_AF-OPEN_PRICE_2','DY-BASIC-MARKET_VALUE']]\n",
    "data.columns=[\"open\",\"high\",\"low\",\"close\",\"市值\"]\n",
    "data.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "3e536ced",
   "metadata": {},
   "outputs": [
    {
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       "      <th>3</th>\n",
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       "         DATE    CODE      open      high       low     close            市值\n",
       "0  2010-01-04  000001   978.291  1014.188   977.053  1011.712  7.362983e+10\n",
       "1  2010-01-04  000002  1074.195  1101.557  1074.195  1099.530  1.165492e+11\n",
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       "3  2010-01-04  000005    58.858    59.448    58.072    59.055  5.476858e+09\n",
       "4  2010-01-04  000006   222.885   227.495   222.685   227.094  5.639878e+09"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data=data.reset_index()\n",
    "data.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "e87a885b",
   "metadata": {},
   "outputs": [
    {
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       "      <td>59.448</td>\n",
       "      <td>58.072</td>\n",
       "      <td>59.055</td>\n",
       "      <td>5.476858e+09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2010-01-04</td>\n",
       "      <td>000006</td>\n",
       "      <td>222.885</td>\n",
       "      <td>227.495</td>\n",
       "      <td>222.685</td>\n",
       "      <td>227.094</td>\n",
       "      <td>5.639878e+09</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        DATE    CODE      open      high       low     close            市值\n",
       "0 2010-01-04  000001   978.291  1014.188   977.053  1011.712  7.362983e+10\n",
       "1 2010-01-04  000002  1074.195  1101.557  1074.195  1099.530  1.165492e+11\n",
       "2 2010-01-04  000004    68.339     0.000     0.000     0.000  8.397668e+08\n",
       "3 2010-01-04  000005    58.858    59.448    58.072    59.055  5.476858e+09\n",
       "4 2010-01-04  000006   222.885   227.495   222.685   227.094  5.639878e+09"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data[\"DATE\"]=pd.to_datetime(data[\"DATE\"])\n",
    "data.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4ac1fae6",
   "metadata": {},
   "source": [
    "> sus"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "bd0fe9c7",
   "metadata": {},
   "outputs": [
    {
     "data": {
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      "text/plain": [
       "     股票代码         日期  是否停牌\n",
       "0  000001 2010-01-04     0\n",
       "1  000002 2010-01-04     0\n",
       "2  000004 2010-01-04     1\n",
       "3  000005 2010-01-04     0\n",
       "4  000006 2010-01-04     0"
      ]
     },
     "execution_count": 12,
     "metadata": {},
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    }
   ],
   "source": [
    "parquet_file = pq.ParquetFile(r'basic_data\\停牌.parquet')\n",
    "sus = parquet_file.read().to_pandas()\n",
    "sus.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "7ee6e8e0",
   "metadata": {},
   "outputs": [
    {
     "data": {
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      "text/plain": [
       "     股票代码         日期  是否停牌\n",
       "0  000001 2010-01-04     0\n",
       "1  000002 2010-01-04     0\n",
       "2  000004 2010-01-04     1\n",
       "3  000005 2010-01-04     0\n",
       "4  000006 2010-01-04     0"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
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   ],
   "source": [
    "sus[\"日期\"]=pd.to_datetime(sus[\"日期\"])\n",
    "sus.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "4b523cab",
   "metadata": {},
   "outputs": [
    {
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       "           CODE       DATE  是否停牌\n",
       "0        000001 2010-01-04     0\n",
       "1        000002 2010-01-04     0\n",
       "2        000004 2010-01-04     1\n",
       "3        000005 2010-01-04     0\n",
       "4        000006 2010-01-04     0\n",
       "...         ...        ...   ...\n",
       "8730451  871396 2021-12-31     0\n",
       "8730452  871553 2021-12-31     0\n",
       "8730453  871642 2021-12-31     0\n",
       "8730454  871981 2021-12-31     0\n",
       "8730455  872925 2021-12-31     0\n",
       "\n",
       "[8730456 rows x 3 columns]"
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     },
     "execution_count": 14,
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   "source": [
    "sus.columns=[\"CODE\",\"DATE\",\"是否停牌\"]\n",
    "sus"
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  {
   "cell_type": "markdown",
   "id": "d861b156",
   "metadata": {},
   "source": [
    "> ind"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "f071bd6d",
   "metadata": {},
   "outputs": [
    {
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       "      <td>银行</td>\n",
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      ],
      "text/plain": [
       "                        TYPE_ID LEVEL1_NAME LEVEL2_NAME LEVEL3_NAME\n",
       "CODE   DATE                                                        \n",
       "000001 20100104  DY010321330101        金融服务          银行          银行\n",
       "       20100105  DY010321330101        金融服务          银行          银行\n",
       "       20100106  DY010321330101        金融服务          银行          银行\n",
       "       20100107  DY010321330101        金融服务          银行          银行\n",
       "       20100108  DY010321330101        金融服务          银行          银行"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "parquet_file = pq.ParquetFile(r'basic_data\\industry.parquet')\n",
    "industry = parquet_file.read().to_pandas()\n",
    "industry.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "cf66b3f1",
   "metadata": {},
   "outputs": [
    {
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       "      <td>银行</td>\n",
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       "      <td>000001</td>\n",
       "      <td>20100108</td>\n",
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       "      <td>金融服务</td>\n",
       "      <td>银行</td>\n",
       "      <td>银行</td>\n",
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      ],
      "text/plain": [
       "     CODE      DATE         TYPE_ID LEVEL1_NAME LEVEL2_NAME LEVEL3_NAME\n",
       "0  000001  20100104  DY010321330101        金融服务          银行          银行\n",
       "1  000001  20100105  DY010321330101        金融服务          银行          银行\n",
       "2  000001  20100106  DY010321330101        金融服务          银行          银行\n",
       "3  000001  20100107  DY010321330101        金融服务          银行          银行\n",
       "4  000001  20100108  DY010321330101        金融服务          银行          银行"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "industry=industry.reset_index()\n",
    "industry.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "34d20073",
   "metadata": {},
   "outputs": [
    {
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       "      <td>DY010321330101</td>\n",
       "      <td>金融服务</td>\n",
       "      <td>银行</td>\n",
       "      <td>银行</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>000001</td>\n",
       "      <td>2010-01-08</td>\n",
       "      <td>DY010321330101</td>\n",
       "      <td>金融服务</td>\n",
       "      <td>银行</td>\n",
       "      <td>银行</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     CODE       DATE         TYPE_ID LEVEL1_NAME LEVEL2_NAME LEVEL3_NAME\n",
       "0  000001 2010-01-04  DY010321330101        金融服务          银行          银行\n",
       "1  000001 2010-01-05  DY010321330101        金融服务          银行          银行\n",
       "2  000001 2010-01-06  DY010321330101        金融服务          银行          银行\n",
       "3  000001 2010-01-07  DY010321330101        金融服务          银行          银行\n",
       "4  000001 2010-01-08  DY010321330101        金融服务          银行          银行"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "industry[\"DATE\"]=pd.to_datetime(industry[\"DATE\"])\n",
    "industry.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e6b26cca",
   "metadata": {},
   "source": [
    "> st"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "f9b9b7a0",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th>000001</th>\n",
       "      <th>000002</th>\n",
       "      <th>000003</th>\n",
       "      <th>000004</th>\n",
       "      <th>000005</th>\n",
       "      <th>000006</th>\n",
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       "      <th>688789</th>\n",
       "      <th>688793</th>\n",
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       "      <th>688819</th>\n",
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       "      <th>689009</th>\n",
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       "      <th>20100104</th>\n",
       "      <td>None</td>\n",
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       "      <td>Y</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>S</td>\n",
       "      <td>S</td>\n",
       "      <td>None</td>\n",
       "      <td>S</td>\n",
       "      <td>...</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20100105</th>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>T</td>\n",
       "      <td>Y</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>S</td>\n",
       "      <td>S</td>\n",
       "      <td>None</td>\n",
       "      <td>S</td>\n",
       "      <td>...</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20100106</th>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>T</td>\n",
       "      <td>Y</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>S</td>\n",
       "      <td>S</td>\n",
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       "      <td>S</td>\n",
       "      <td>...</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20100107</th>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>T</td>\n",
       "      <td>Y</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>S</td>\n",
       "      <td>S</td>\n",
       "      <td>None</td>\n",
       "      <td>S</td>\n",
       "      <td>...</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20100108</th>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>T</td>\n",
       "      <td>Y</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>S</td>\n",
       "      <td>S</td>\n",
       "      <td>None</td>\n",
       "      <td>S</td>\n",
       "      <td>...</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 5370 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "         000001 000002 000003 000004 000005 000006 000007 000008 000009  \\\n",
       "20100104   None   None      T      Y   None   None      S      S   None   \n",
       "20100105   None   None      T      Y   None   None      S      S   None   \n",
       "20100106   None   None      T      Y   None   None      S      S   None   \n",
       "20100107   None   None      T      Y   None   None      S      S   None   \n",
       "20100108   None   None      T      Y   None   None      S      S   None   \n",
       "\n",
       "         000010  ... 688787 688788 688789 688793 688798 688799 688800 688819  \\\n",
       "20100104      S  ...   None   None   None   None   None   None   None   None   \n",
       "20100105      S  ...   None   None   None   None   None   None   None   None   \n",
       "20100106      S  ...   None   None   None   None   None   None   None   None   \n",
       "20100107      S  ...   None   None   None   None   None   None   None   None   \n",
       "20100108      S  ...   None   None   None   None   None   None   None   None   \n",
       "\n",
       "         688981 689009  \n",
       "20100104   None   None  \n",
       "20100105   None   None  \n",
       "20100106   None   None  \n",
       "20100107   None   None  \n",
       "20100108   None   None  \n",
       "\n",
       "[5 rows x 5370 columns]"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "parquet_file = pq.ParquetFile(r'basic_data\\st.parquet')\n",
    "st = parquet_file.read().to_pandas()\n",
    "st.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "746fd8c7",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>date</th>\n",
       "      <th>stock_code</th>\n",
       "      <th>value</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>20100104</td>\n",
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       "      <th>1</th>\n",
       "      <td>20100105</td>\n",
       "      <td>000001</td>\n",
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       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>20100106</td>\n",
       "      <td>000001</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>20100107</td>\n",
       "      <td>000001</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>20100108</td>\n",
       "      <td>000001</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       date stock_code value\n",
       "0  20100104     000001  None\n",
       "1  20100105     000001  None\n",
       "2  20100106     000001  None\n",
       "3  20100107     000001  None\n",
       "4  20100108     000001  None"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "st = st.reset_index().rename(columns={'index': 'date'})  \n",
    "st = st.melt(id_vars='date', var_name='stock_code', value_name='value')\n",
    "st.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "069b2d91",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>date</th>\n",
       "      <th>stock_code</th>\n",
       "      <th>value</th>\n",
       "    </tr>\n",
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       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2010-01-04</td>\n",
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       "      <td>None</td>\n",
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       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2010-01-05</td>\n",
       "      <td>000001</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2010-01-06</td>\n",
       "      <td>000001</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2010-01-07</td>\n",
       "      <td>000001</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2010-01-08</td>\n",
       "      <td>000001</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        date stock_code value\n",
       "0 2010-01-04     000001  None\n",
       "1 2010-01-05     000001  None\n",
       "2 2010-01-06     000001  None\n",
       "3 2010-01-07     000001  None\n",
       "4 2010-01-08     000001  None"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "st[\"date\"]=pd.to_datetime(st[\"date\"])\n",
    "st.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "db2dd916",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>DATE</th>\n",
       "      <th>CODE</th>\n",
       "      <th>ST</th>\n",
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       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2010-01-04</td>\n",
       "      <td>000001</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2010-01-05</td>\n",
       "      <td>000001</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2010-01-06</td>\n",
       "      <td>000001</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2010-01-07</td>\n",
       "      <td>000001</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2010-01-08</td>\n",
       "      <td>000001</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        DATE    CODE    ST\n",
       "0 2010-01-04  000001  None\n",
       "1 2010-01-05  000001  None\n",
       "2 2010-01-06  000001  None\n",
       "3 2010-01-07  000001  None\n",
       "4 2010-01-08  000001  None"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "st.columns=[\"DATE\",\"CODE\",\"ST\"]\n",
    "st.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d5f0971b",
   "metadata": {},
   "source": [
    "## **二、计算因子和t1日是否涨跌停指标**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "a758a64c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>DATE</th>\n",
       "      <th>CODE</th>\n",
       "      <th>open</th>\n",
       "      <th>high</th>\n",
       "      <th>low</th>\n",
       "      <th>close</th>\n",
       "      <th>市值</th>\n",
       "      <th>因子</th>\n",
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       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2010-01-04</td>\n",
       "      <td>000001</td>\n",
       "      <td>978.291</td>\n",
       "      <td>1014.188</td>\n",
       "      <td>977.053</td>\n",
       "      <td>1011.712</td>\n",
       "      <td>7.362983e+10</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2010-01-04</td>\n",
       "      <td>000002</td>\n",
       "      <td>1074.195</td>\n",
       "      <td>1101.557</td>\n",
       "      <td>1074.195</td>\n",
       "      <td>1099.530</td>\n",
       "      <td>1.165492e+11</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2010-01-04</td>\n",
       "      <td>000004</td>\n",
       "      <td>68.339</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>8.397668e+08</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2010-01-04</td>\n",
       "      <td>000005</td>\n",
       "      <td>58.858</td>\n",
       "      <td>59.448</td>\n",
       "      <td>58.072</td>\n",
       "      <td>59.055</td>\n",
       "      <td>5.476858e+09</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2010-01-04</td>\n",
       "      <td>000006</td>\n",
       "      <td>222.885</td>\n",
       "      <td>227.495</td>\n",
       "      <td>222.685</td>\n",
       "      <td>227.094</td>\n",
       "      <td>5.639878e+09</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        DATE    CODE      open      high       low     close            市值  因子\n",
       "0 2010-01-04  000001   978.291  1014.188   977.053  1011.712  7.362983e+10 NaN\n",
       "1 2010-01-04  000002  1074.195  1101.557  1074.195  1099.530  1.165492e+11 NaN\n",
       "2 2010-01-04  000004    68.339     0.000     0.000     0.000  8.397668e+08 NaN\n",
       "3 2010-01-04  000005    58.858    59.448    58.072    59.055  5.476858e+09 NaN\n",
       "4 2010-01-04  000006   222.885   227.495   222.685   227.094  5.639878e+09 NaN"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data[\"因子\"]=data.groupby(\"CODE\",as_index=False).apply(lambda x:x[\"close\"]/x[\"close\"].shift(5)-1).reset_index(level=0,drop=True)\n",
    "data.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "3bb27d8c",
   "metadata": {},
   "outputs": [],
   "source": [
    "#将inf值置空\n",
    "data.loc[data[\"因子\"] == np.inf, \"因子\"] = np.nan\n",
    "data.loc[data[\"因子\"] == -np.inf, \"因子\"] = np.nan"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "d2c29af8",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <td>977.053</td>\n",
       "      <td>1011.712</td>\n",
       "      <td>7.362983e+10</td>\n",
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       "      <th>1</th>\n",
       "      <td>2010-01-04</td>\n",
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       "      <td>1074.195</td>\n",
       "      <td>1101.557</td>\n",
       "      <td>1074.195</td>\n",
       "      <td>1099.530</td>\n",
       "      <td>1.165492e+11</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.032351</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2010-01-04</td>\n",
       "      <td>000004</td>\n",
       "      <td>68.339</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>8.397668e+08</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2010-01-04</td>\n",
       "      <td>000005</td>\n",
       "      <td>58.858</td>\n",
       "      <td>59.448</td>\n",
       "      <td>58.072</td>\n",
       "      <td>59.055</td>\n",
       "      <td>5.476858e+09</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.010092</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2010-01-04</td>\n",
       "      <td>000006</td>\n",
       "      <td>222.885</td>\n",
       "      <td>227.495</td>\n",
       "      <td>222.685</td>\n",
       "      <td>227.094</td>\n",
       "      <td>5.639878e+09</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.018884</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        DATE    CODE      open      high       low     close            市值  \\\n",
       "0 2010-01-04  000001   978.291  1014.188   977.053  1011.712  7.362983e+10   \n",
       "1 2010-01-04  000002  1074.195  1101.557  1074.195  1099.530  1.165492e+11   \n",
       "2 2010-01-04  000004    68.339     0.000     0.000     0.000  8.397668e+08   \n",
       "3 2010-01-04  000005    58.858    59.448    58.072    59.055  5.476858e+09   \n",
       "4 2010-01-04  000006   222.885   227.495   222.685   227.094  5.639878e+09   \n",
       "\n",
       "   因子     次日涨跌幅  \n",
       "0 NaN  0.032420  \n",
       "1 NaN  0.032351  \n",
       "2 NaN       NaN  \n",
       "3 NaN  0.010092  \n",
       "4 NaN  0.018884  "
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data[\"次日涨跌幅\"]=data.groupby(\"CODE\",as_index=False).apply(lambda x:x[\"close\"].pct_change(-1)).reset_index(level=0,drop=True)\n",
    "data.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "0c484640",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th>1</th>\n",
       "      <td>2010-01-04</td>\n",
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       "      <td>1101.557</td>\n",
       "      <td>1074.195</td>\n",
       "      <td>1099.530</td>\n",
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       "      <td>NaN</td>\n",
       "      <td>0.032351</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2010-01-04</td>\n",
       "      <td>000004</td>\n",
       "      <td>68.339</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>8.397668e+08</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2010-01-04</td>\n",
       "      <td>000005</td>\n",
       "      <td>58.858</td>\n",
       "      <td>59.448</td>\n",
       "      <td>58.072</td>\n",
       "      <td>59.055</td>\n",
       "      <td>5.476858e+09</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.010092</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2010-01-04</td>\n",
       "      <td>000006</td>\n",
       "      <td>222.885</td>\n",
       "      <td>227.495</td>\n",
       "      <td>222.685</td>\n",
       "      <td>227.094</td>\n",
       "      <td>5.639878e+09</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.018884</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        DATE    CODE      open      high       low     close            市值  \\\n",
       "0 2010-01-04  000001   978.291  1014.188   977.053  1011.712  7.362983e+10   \n",
       "1 2010-01-04  000002  1074.195  1101.557  1074.195  1099.530  1.165492e+11   \n",
       "2 2010-01-04  000004    68.339     0.000     0.000     0.000  8.397668e+08   \n",
       "3 2010-01-04  000005    58.858    59.448    58.072    59.055  5.476858e+09   \n",
       "4 2010-01-04  000006   222.885   227.495   222.685   227.094  5.639878e+09   \n",
       "\n",
       "   因子     次日涨跌幅  \n",
       "0 NaN  0.032420  \n",
       "1 NaN  0.032351  \n",
       "2 NaN       NaN  \n",
       "3 NaN  0.010092  \n",
       "4 NaN  0.018884  "
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data[\"次日涨跌幅\"]=abs(data[\"次日涨跌幅\"])\n",
    "data.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "bd2b845c",
   "metadata": {},
   "outputs": [],
   "source": [
    "#将inf值置空\n",
    "data.loc[data[\"次日涨跌幅\"] == np.inf, \"次日涨跌幅\"] = np.nan\n",
    "data.loc[data[\"次日涨跌幅\"] == -np.inf, \"次日涨跌幅\"] = np.nan"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c3c67e69",
   "metadata": {},
   "source": [
    "> 考虑到所有数据并没有做复权，又可能会有分红等情况的发生导致价格突变，所以把0.095作为涨跌停的阈值，如果大于则置空"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "c08ecf63",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "      <th>DATE</th>\n",
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       "      <td>2010-01-04</td>\n",
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       "      <td>977.053</td>\n",
       "      <td>1011.712</td>\n",
       "      <td>7.362983e+10</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.032420</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2010-01-04</td>\n",
       "      <td>000002</td>\n",
       "      <td>1074.195</td>\n",
       "      <td>1101.557</td>\n",
       "      <td>1074.195</td>\n",
       "      <td>1099.530</td>\n",
       "      <td>1.165492e+11</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.032351</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2010-01-04</td>\n",
       "      <td>000004</td>\n",
       "      <td>68.339</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>8.397668e+08</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2010-01-04</td>\n",
       "      <td>000005</td>\n",
       "      <td>58.858</td>\n",
       "      <td>59.448</td>\n",
       "      <td>58.072</td>\n",
       "      <td>59.055</td>\n",
       "      <td>5.476858e+09</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.010092</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2010-01-04</td>\n",
       "      <td>000006</td>\n",
       "      <td>222.885</td>\n",
       "      <td>227.495</td>\n",
       "      <td>222.685</td>\n",
       "      <td>227.094</td>\n",
       "      <td>5.639878e+09</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.018884</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        DATE    CODE      open      high       low     close            市值  \\\n",
       "0 2010-01-04  000001   978.291  1014.188   977.053  1011.712  7.362983e+10   \n",
       "1 2010-01-04  000002  1074.195  1101.557  1074.195  1099.530  1.165492e+11   \n",
       "2 2010-01-04  000004    68.339     0.000     0.000     0.000  8.397668e+08   \n",
       "3 2010-01-04  000005    58.858    59.448    58.072    59.055  5.476858e+09   \n",
       "4 2010-01-04  000006   222.885   227.495   222.685   227.094  5.639878e+09   \n",
       "\n",
       "   因子     次日涨跌幅  \n",
       "0 NaN  0.032420  \n",
       "1 NaN  0.032351  \n",
       "2 NaN       NaN  \n",
       "3 NaN  0.010092  \n",
       "4 NaN  0.018884  "
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data[\"次日涨跌幅\"] = data[\"次日涨跌幅\"].apply(lambda x: np.nan if x > 0.095 else x)\n",
    "data.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d6c61e53",
   "metadata": {},
   "source": [
    "## **三、计算剔除过后的收益率**"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1bb75848",
   "metadata": {},
   "source": [
    "### **1.进行合并操作**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "56170861",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <td>1101.557</td>\n",
       "      <td>1074.195</td>\n",
       "      <td>1099.530</td>\n",
       "      <td>1.165492e+11</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.032351</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2010-01-04</td>\n",
       "      <td>000004</td>\n",
       "      <td>68.339</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>8.397668e+08</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2010-01-04</td>\n",
       "      <td>000005</td>\n",
       "      <td>58.858</td>\n",
       "      <td>59.448</td>\n",
       "      <td>58.072</td>\n",
       "      <td>59.055</td>\n",
       "      <td>5.476858e+09</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.010092</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2010-01-04</td>\n",
       "      <td>000006</td>\n",
       "      <td>222.885</td>\n",
       "      <td>227.495</td>\n",
       "      <td>222.685</td>\n",
       "      <td>227.094</td>\n",
       "      <td>5.639878e+09</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.018884</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        DATE    CODE      open      high       low     close            市值  \\\n",
       "0 2010-01-04  000001   978.291  1014.188   977.053  1011.712  7.362983e+10   \n",
       "1 2010-01-04  000002  1074.195  1101.557  1074.195  1099.530  1.165492e+11   \n",
       "2 2010-01-04  000004    68.339     0.000     0.000     0.000  8.397668e+08   \n",
       "3 2010-01-04  000005    58.858    59.448    58.072    59.055  5.476858e+09   \n",
       "4 2010-01-04  000006   222.885   227.495   222.685   227.094  5.639878e+09   \n",
       "\n",
       "   因子     次日涨跌幅  是否停牌  \n",
       "0 NaN  0.032420     0  \n",
       "1 NaN  0.032351     0  \n",
       "2 NaN       NaN     1  \n",
       "3 NaN  0.010092     0  \n",
       "4 NaN  0.018884     0  "
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data=pd.merge(data,sus,on=['DATE', 'CODE'])\n",
    "data.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "be4343b4",
   "metadata": {},
   "outputs": [
    {
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       "        DATE    CODE      open      high       low     close            市值  \\\n",
       "0 2010-01-04  000001   978.291  1014.188   977.053  1011.712  7.362983e+10   \n",
       "1 2010-01-04  000002  1074.195  1101.557  1074.195  1099.530  1.165492e+11   \n",
       "2 2010-01-04  000004    68.339     0.000     0.000     0.000  8.397668e+08   \n",
       "3 2010-01-04  000005    58.858    59.448    58.072    59.055  5.476858e+09   \n",
       "4 2010-01-04  000006   222.885   227.495   222.685   227.094  5.639878e+09   \n",
       "\n",
       "   因子     次日涨跌幅  是否停牌    ST  \n",
       "0 NaN  0.032420     0  None  \n",
       "1 NaN  0.032351     0  None  \n",
       "2 NaN       NaN     1     Y  \n",
       "3 NaN  0.010092     0  None  \n",
       "4 NaN  0.018884     0  None  "
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data=pd.merge(data,st,on=['DATE', 'CODE'])\n",
    "data.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "id": "b71dff4e",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <td>2010-01-04</td>\n",
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       "      <td>NaN</td>\n",
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       "      <td>Y</td>\n",
       "      <td>DY010321170301</td>\n",
       "      <td>医药生物</td>\n",
       "      <td>生物制品</td>\n",
       "      <td>生物制品</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2010-01-04</td>\n",
       "      <td>000005</td>\n",
       "      <td>58.858</td>\n",
       "      <td>59.448</td>\n",
       "      <td>58.072</td>\n",
       "      <td>59.055</td>\n",
       "      <td>5.476858e+09</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.010092</td>\n",
       "      <td>0</td>\n",
       "      <td>None</td>\n",
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       "      <td>房地产</td>\n",
       "      <td>房地产开发</td>\n",
       "      <td>住宅开发</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2010-01-04</td>\n",
       "      <td>000006</td>\n",
       "      <td>222.885</td>\n",
       "      <td>227.495</td>\n",
       "      <td>222.685</td>\n",
       "      <td>227.094</td>\n",
       "      <td>5.639878e+09</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.018884</td>\n",
       "      <td>0</td>\n",
       "      <td>None</td>\n",
       "      <td>DY010321200101</td>\n",
       "      <td>房地产</td>\n",
       "      <td>房地产开发</td>\n",
       "      <td>住宅开发</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        DATE    CODE      open      high       low     close            市值  \\\n",
       "0 2010-01-04  000001   978.291  1014.188   977.053  1011.712  7.362983e+10   \n",
       "1 2010-01-04  000002  1074.195  1101.557  1074.195  1099.530  1.165492e+11   \n",
       "2 2010-01-04  000004    68.339     0.000     0.000     0.000  8.397668e+08   \n",
       "3 2010-01-04  000005    58.858    59.448    58.072    59.055  5.476858e+09   \n",
       "4 2010-01-04  000006   222.885   227.495   222.685   227.094  5.639878e+09   \n",
       "\n",
       "   因子     次日涨跌幅  是否停牌    ST         TYPE_ID LEVEL1_NAME LEVEL2_NAME  \\\n",
       "0 NaN  0.032420     0  None  DY010321330101        金融服务          银行   \n",
       "1 NaN  0.032351     0  None  DY010321200101         房地产       房地产开发   \n",
       "2 NaN       NaN     1     Y  DY010321170301        医药生物        生物制品   \n",
       "3 NaN  0.010092     0  None  DY010321200101         房地产       房地产开发   \n",
       "4 NaN  0.018884     0  None  DY010321200101         房地产       房地产开发   \n",
       "\n",
       "  LEVEL3_NAME  \n",
       "0          银行  \n",
       "1        住宅开发  \n",
       "2        生物制品  \n",
       "3        住宅开发  \n",
       "4        住宅开发  "
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data=pd.merge(data,industry,on=['DATE', 'CODE'])\n",
    "data.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "bcf0bdca",
   "metadata": {},
   "source": [
    "### **2.进行替换操作**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "id": "2cdd2c3e",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <td>房地产开发</td>\n",
       "      <td>住宅开发</td>\n",
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       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2010-01-04</td>\n",
       "      <td>000004</td>\n",
       "      <td>68.339</td>\n",
       "      <td>0.000</td>\n",
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       "      <td>0.000</td>\n",
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       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Y</td>\n",
       "      <td>DY010321170301</td>\n",
       "      <td>医药生物</td>\n",
       "      <td>生物制品</td>\n",
       "      <td>生物制品</td>\n",
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       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2010-01-04</td>\n",
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       "      <td>59.448</td>\n",
       "      <td>58.072</td>\n",
       "      <td>59.055</td>\n",
       "      <td>5.476858e+09</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.010092</td>\n",
       "      <td>0.0</td>\n",
       "      <td>None</td>\n",
       "      <td>DY010321200101</td>\n",
       "      <td>房地产</td>\n",
       "      <td>房地产开发</td>\n",
       "      <td>住宅开发</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2010-01-04</td>\n",
       "      <td>000006</td>\n",
       "      <td>222.885</td>\n",
       "      <td>227.495</td>\n",
       "      <td>222.685</td>\n",
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       "      <td>5.639878e+09</td>\n",
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       "      <td>DY010321200101</td>\n",
       "      <td>房地产</td>\n",
       "      <td>房地产开发</td>\n",
       "      <td>住宅开发</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        DATE    CODE      open      high       low     close            市值  \\\n",
       "0 2010-01-04  000001   978.291  1014.188   977.053  1011.712  7.362983e+10   \n",
       "1 2010-01-04  000002  1074.195  1101.557  1074.195  1099.530  1.165492e+11   \n",
       "2 2010-01-04  000004    68.339     0.000     0.000     0.000  8.397668e+08   \n",
       "3 2010-01-04  000005    58.858    59.448    58.072    59.055  5.476858e+09   \n",
       "4 2010-01-04  000006   222.885   227.495   222.685   227.094  5.639878e+09   \n",
       "\n",
       "   因子     次日涨跌幅  是否停牌    ST         TYPE_ID LEVEL1_NAME LEVEL2_NAME  \\\n",
       "0 NaN  0.032420   0.0  None  DY010321330101        金融服务          银行   \n",
       "1 NaN  0.032351   0.0  None  DY010321200101         房地产       房地产开发   \n",
       "2 NaN       NaN   NaN     Y  DY010321170301        医药生物        生物制品   \n",
       "3 NaN  0.010092   0.0  None  DY010321200101         房地产       房地产开发   \n",
       "4 NaN  0.018884   0.0  None  DY010321200101         房地产       房地产开发   \n",
       "\n",
       "  LEVEL3_NAME  \n",
       "0          银行  \n",
       "1        住宅开发  \n",
       "2        生物制品  \n",
       "3        住宅开发  \n",
       "4        住宅开发  "
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data[\"是否停牌\"]=data[\"是否停牌\"].replace({1:np.nan})\n",
    "data.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "id": "e2041094",
   "metadata": {},
   "outputs": [
    {
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       "      <td>978.291</td>\n",
       "      <td>1014.188</td>\n",
       "      <td>977.053</td>\n",
       "      <td>1011.712</td>\n",
       "      <td>7.362983e+10</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.032420</td>\n",
       "      <td>0.0</td>\n",
       "      <td>None</td>\n",
       "      <td>DY010321330101</td>\n",
       "      <td>金融服务</td>\n",
       "      <td>银行</td>\n",
       "      <td>银行</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2010-01-04</td>\n",
       "      <td>000002</td>\n",
       "      <td>1074.195</td>\n",
       "      <td>1101.557</td>\n",
       "      <td>1074.195</td>\n",
       "      <td>1099.530</td>\n",
       "      <td>1.165492e+11</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.032351</td>\n",
       "      <td>0.0</td>\n",
       "      <td>None</td>\n",
       "      <td>DY010321200101</td>\n",
       "      <td>房地产</td>\n",
       "      <td>房地产开发</td>\n",
       "      <td>住宅开发</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2010-01-04</td>\n",
       "      <td>000004</td>\n",
       "      <td>68.339</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>8.397668e+08</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>DY010321170301</td>\n",
       "      <td>医药生物</td>\n",
       "      <td>生物制品</td>\n",
       "      <td>生物制品</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2010-01-04</td>\n",
       "      <td>000005</td>\n",
       "      <td>58.858</td>\n",
       "      <td>59.448</td>\n",
       "      <td>58.072</td>\n",
       "      <td>59.055</td>\n",
       "      <td>5.476858e+09</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.010092</td>\n",
       "      <td>0.0</td>\n",
       "      <td>None</td>\n",
       "      <td>DY010321200101</td>\n",
       "      <td>房地产</td>\n",
       "      <td>房地产开发</td>\n",
       "      <td>住宅开发</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2010-01-04</td>\n",
       "      <td>000006</td>\n",
       "      <td>222.885</td>\n",
       "      <td>227.495</td>\n",
       "      <td>222.685</td>\n",
       "      <td>227.094</td>\n",
       "      <td>5.639878e+09</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.018884</td>\n",
       "      <td>0.0</td>\n",
       "      <td>None</td>\n",
       "      <td>DY010321200101</td>\n",
       "      <td>房地产</td>\n",
       "      <td>房地产开发</td>\n",
       "      <td>住宅开发</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        DATE    CODE      open      high       low     close            市值  \\\n",
       "0 2010-01-04  000001   978.291  1014.188   977.053  1011.712  7.362983e+10   \n",
       "1 2010-01-04  000002  1074.195  1101.557  1074.195  1099.530  1.165492e+11   \n",
       "2 2010-01-04  000004    68.339     0.000     0.000     0.000  8.397668e+08   \n",
       "3 2010-01-04  000005    58.858    59.448    58.072    59.055  5.476858e+09   \n",
       "4 2010-01-04  000006   222.885   227.495   222.685   227.094  5.639878e+09   \n",
       "\n",
       "   因子     次日涨跌幅  是否停牌    ST         TYPE_ID LEVEL1_NAME LEVEL2_NAME  \\\n",
       "0 NaN  0.032420   0.0  None  DY010321330101        金融服务          银行   \n",
       "1 NaN  0.032351   0.0  None  DY010321200101         房地产       房地产开发   \n",
       "2 NaN       NaN   NaN   NaN  DY010321170301        医药生物        生物制品   \n",
       "3 NaN  0.010092   0.0  None  DY010321200101         房地产       房地产开发   \n",
       "4 NaN  0.018884   0.0  None  DY010321200101         房地产       房地产开发   \n",
       "\n",
       "  LEVEL3_NAME  \n",
       "0          银行  \n",
       "1        住宅开发  \n",
       "2        生物制品  \n",
       "3        住宅开发  \n",
       "4        住宅开发  "
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.loc[data[\"ST\"].notna(), \"ST\"] = np.nan\n",
    "data.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "id": "16da8dce",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>DATE</th>\n",
       "      <th>CODE</th>\n",
       "      <th>open</th>\n",
       "      <th>high</th>\n",
       "      <th>low</th>\n",
       "      <th>close</th>\n",
       "      <th>市值</th>\n",
       "      <th>因子</th>\n",
       "      <th>次日涨跌幅</th>\n",
       "      <th>是否停牌</th>\n",
       "      <th>ST</th>\n",
       "      <th>TYPE_ID</th>\n",
       "      <th>LEVEL1_NAME</th>\n",
       "      <th>LEVEL2_NAME</th>\n",
       "      <th>LEVEL3_NAME</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2010-01-04</td>\n",
       "      <td>000001</td>\n",
       "      <td>978.291</td>\n",
       "      <td>1014.188</td>\n",
       "      <td>977.053</td>\n",
       "      <td>1011.712</td>\n",
       "      <td>7.362983e+10</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.032420</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>DY010321330101</td>\n",
       "      <td>金融服务</td>\n",
       "      <td>银行</td>\n",
       "      <td>银行</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2010-01-04</td>\n",
       "      <td>000002</td>\n",
       "      <td>1074.195</td>\n",
       "      <td>1101.557</td>\n",
       "      <td>1074.195</td>\n",
       "      <td>1099.530</td>\n",
       "      <td>1.165492e+11</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.032351</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>DY010321200101</td>\n",
       "      <td>房地产</td>\n",
       "      <td>房地产开发</td>\n",
       "      <td>住宅开发</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2010-01-04</td>\n",
       "      <td>000004</td>\n",
       "      <td>68.339</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>8.397668e+08</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>DY010321170301</td>\n",
       "      <td>医药生物</td>\n",
       "      <td>生物制品</td>\n",
       "      <td>生物制品</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2010-01-04</td>\n",
       "      <td>000005</td>\n",
       "      <td>58.858</td>\n",
       "      <td>59.448</td>\n",
       "      <td>58.072</td>\n",
       "      <td>59.055</td>\n",
       "      <td>5.476858e+09</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.010092</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>DY010321200101</td>\n",
       "      <td>房地产</td>\n",
       "      <td>房地产开发</td>\n",
       "      <td>住宅开发</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2010-01-04</td>\n",
       "      <td>000006</td>\n",
       "      <td>222.885</td>\n",
       "      <td>227.495</td>\n",
       "      <td>222.685</td>\n",
       "      <td>227.094</td>\n",
       "      <td>5.639878e+09</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.018884</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>DY010321200101</td>\n",
       "      <td>房地产</td>\n",
       "      <td>房地产开发</td>\n",
       "      <td>住宅开发</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        DATE    CODE      open      high       low     close            市值  \\\n",
       "0 2010-01-04  000001   978.291  1014.188   977.053  1011.712  7.362983e+10   \n",
       "1 2010-01-04  000002  1074.195  1101.557  1074.195  1099.530  1.165492e+11   \n",
       "2 2010-01-04  000004    68.339     0.000     0.000     0.000  8.397668e+08   \n",
       "3 2010-01-04  000005    58.858    59.448    58.072    59.055  5.476858e+09   \n",
       "4 2010-01-04  000006   222.885   227.495   222.685   227.094  5.639878e+09   \n",
       "\n",
       "   因子     次日涨跌幅  是否停牌   ST         TYPE_ID LEVEL1_NAME LEVEL2_NAME LEVEL3_NAME  \n",
       "0 NaN  0.032420   0.0  0.0  DY010321330101        金融服务          银行          银行  \n",
       "1 NaN  0.032351   0.0  0.0  DY010321200101         房地产       房地产开发        住宅开发  \n",
       "2 NaN       NaN   NaN  NaN  DY010321170301        医药生物        生物制品        生物制品  \n",
       "3 NaN  0.010092   0.0  0.0  DY010321200101         房地产       房地产开发        住宅开发  \n",
       "4 NaN  0.018884   0.0  0.0  DY010321200101         房地产       房地产开发        住宅开发  "
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#将所有的None变为0，防止误触判断条件\n",
    "data[\"ST\"] = data[\"ST\"].apply(lambda x: 0 if x is None else x)\n",
    "data.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ca8aa38c",
   "metadata": {},
   "source": [
    "### **3.将t1日涨跌停和停牌、t0日为st以及上市不满60天的股票的开盘价置空再计算收益率**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "id": "18138b0b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "DATE           datetime64[ns]\n",
       "CODE                   object\n",
       "open                  float64\n",
       "high                  float64\n",
       "low                   float64\n",
       "close                 float64\n",
       "市值                    float64\n",
       "因子                    float64\n",
       "次日涨跌幅                 float64\n",
       "是否停牌                  float64\n",
       "ST                    float64\n",
       "TYPE_ID                object\n",
       "LEVEL1_NAME            object\n",
       "LEVEL2_NAME            object\n",
       "LEVEL3_NAME            object\n",
       "dtype: object"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.dtypes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "id": "d21f7ad9",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "DATE           datetime64[ns]\n",
       "CODE                   object\n",
       "open                  float32\n",
       "high                  float32\n",
       "low                   float32\n",
       "close                 float32\n",
       "市值                    float32\n",
       "因子                    float32\n",
       "次日涨跌幅                 float32\n",
       "是否停牌                  float32\n",
       "ST                    float32\n",
       "TYPE_ID                object\n",
       "LEVEL1_NAME            object\n",
       "LEVEL2_NAME            object\n",
       "LEVEL3_NAME            object\n",
       "dtype: object"
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#转化为float32减少内存消耗，防止卡机\n",
    "data[[\"是否停牌\",\"ST\",\"open\",\"high\",\"low\",\"close\",\"市值\",\"次日涨跌幅\",\"因子\"]]=data[[\"是否停牌\",\"ST\",\"open\",\"high\",\"low\",\"close\",\"市值\",\"次日涨跌幅\",\"因子\"]].astype(np.float32)\n",
    "data.dtypes"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "bd7dbd41",
   "metadata": {},
   "source": [
    "> 将t1日停牌的股票的开盘价置空"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "id": "1e73558d",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>DATE</th>\n",
       "      <th>CODE</th>\n",
       "      <th>open</th>\n",
       "      <th>high</th>\n",
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       "      <th>close</th>\n",
       "      <th>市值</th>\n",
       "      <th>因子</th>\n",
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       "      <th>是否停牌</th>\n",
       "      <th>ST</th>\n",
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       "      <th>LEVEL2_NAME</th>\n",
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       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2010-01-04</td>\n",
       "      <td>000001</td>\n",
       "      <td>978.291016</td>\n",
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       "      <td>977.052979</td>\n",
       "      <td>1011.711975</td>\n",
       "      <td>7.362984e+10</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.032420</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>DY010321330101</td>\n",
       "      <td>金融服务</td>\n",
       "      <td>银行</td>\n",
       "      <td>银行</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2010-01-04</td>\n",
       "      <td>000002</td>\n",
       "      <td>1074.194946</td>\n",
       "      <td>1101.557007</td>\n",
       "      <td>1074.194946</td>\n",
       "      <td>1099.530029</td>\n",
       "      <td>1.165492e+11</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.032351</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>DY010321200101</td>\n",
       "      <td>房地产</td>\n",
       "      <td>房地产开发</td>\n",
       "      <td>住宅开发</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2010-01-04</td>\n",
       "      <td>000004</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>8.397668e+08</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>DY010321170301</td>\n",
       "      <td>医药生物</td>\n",
       "      <td>生物制品</td>\n",
       "      <td>生物制品</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2010-01-04</td>\n",
       "      <td>000005</td>\n",
       "      <td>58.858002</td>\n",
       "      <td>59.448002</td>\n",
       "      <td>58.071999</td>\n",
       "      <td>59.055000</td>\n",
       "      <td>5.476858e+09</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.010092</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>DY010321200101</td>\n",
       "      <td>房地产</td>\n",
       "      <td>房地产开发</td>\n",
       "      <td>住宅开发</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2010-01-04</td>\n",
       "      <td>000006</td>\n",
       "      <td>222.884995</td>\n",
       "      <td>227.494995</td>\n",
       "      <td>222.684998</td>\n",
       "      <td>227.093994</td>\n",
       "      <td>5.639878e+09</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.018884</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>DY010321200101</td>\n",
       "      <td>房地产</td>\n",
       "      <td>房地产开发</td>\n",
       "      <td>住宅开发</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        DATE    CODE         open         high          low        close  \\\n",
       "0 2010-01-04  000001   978.291016  1014.187988   977.052979  1011.711975   \n",
       "1 2010-01-04  000002  1074.194946  1101.557007  1074.194946  1099.530029   \n",
       "2 2010-01-04  000004          NaN     0.000000     0.000000     0.000000   \n",
       "3 2010-01-04  000005    58.858002    59.448002    58.071999    59.055000   \n",
       "4 2010-01-04  000006   222.884995   227.494995   222.684998   227.093994   \n",
       "\n",
       "             市值  因子     次日涨跌幅  是否停牌   ST         TYPE_ID LEVEL1_NAME  \\\n",
       "0  7.362984e+10 NaN  0.032420   0.0  0.0  DY010321330101        金融服务   \n",
       "1  1.165492e+11 NaN  0.032351   0.0  0.0  DY010321200101         房地产   \n",
       "2  8.397668e+08 NaN       NaN   NaN  NaN  DY010321170301        医药生物   \n",
       "3  5.476858e+09 NaN  0.010092   0.0  0.0  DY010321200101         房地产   \n",
       "4  5.639878e+09 NaN  0.018884   0.0  0.0  DY010321200101         房地产   \n",
       "\n",
       "  LEVEL2_NAME LEVEL3_NAME  \n",
       "0          银行          银行  \n",
       "1       房地产开发        住宅开发  \n",
       "2        生物制品        生物制品  \n",
       "3       房地产开发        住宅开发  \n",
       "4       房地产开发        住宅开发  "
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data[\"open\"]=data.groupby(\"CODE\", as_index=False).apply(\n",
    "    lambda x: pd.Series(\n",
    "        np.where(pd.isna(x[\"是否停牌\"].shift(-1)), np.nan, x[\"open\"]),\n",
    "        index=x.index\n",
    "    )\n",
    ").reset_index(level=0, drop=True)\n",
    "data.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "31eeda6d",
   "metadata": {},
   "source": [
    "> 将t1日涨跌停的股票的开盘价置空"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "id": "6b9fd55f",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <td>住宅开发</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2010-01-04</td>\n",
       "      <td>000004</td>\n",
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       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>DY010321170301</td>\n",
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       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2010-01-04</td>\n",
       "      <td>000005</td>\n",
       "      <td>58.858002</td>\n",
       "      <td>59.448002</td>\n",
       "      <td>58.071999</td>\n",
       "      <td>59.055000</td>\n",
       "      <td>5.476858e+09</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.010092</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
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       "      <td>房地产</td>\n",
       "      <td>房地产开发</td>\n",
       "      <td>住宅开发</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2010-01-04</td>\n",
       "      <td>000006</td>\n",
       "      <td>222.884995</td>\n",
       "      <td>227.494995</td>\n",
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       "      <td>住宅开发</td>\n",
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       "        DATE    CODE         open         high          low        close  \\\n",
       "0 2010-01-04  000001   978.291016  1014.187988   977.052979  1011.711975   \n",
       "1 2010-01-04  000002  1074.194946  1101.557007  1074.194946  1099.530029   \n",
       "2 2010-01-04  000004          NaN     0.000000     0.000000     0.000000   \n",
       "3 2010-01-04  000005    58.858002    59.448002    58.071999    59.055000   \n",
       "4 2010-01-04  000006   222.884995   227.494995   222.684998   227.093994   \n",
       "\n",
       "             市值  因子     次日涨跌幅  是否停牌   ST         TYPE_ID LEVEL1_NAME  \\\n",
       "0  7.362984e+10 NaN  0.032420   0.0  0.0  DY010321330101        金融服务   \n",
       "1  1.165492e+11 NaN  0.032351   0.0  0.0  DY010321200101         房地产   \n",
       "2  8.397668e+08 NaN       NaN   NaN  NaN  DY010321170301        医药生物   \n",
       "3  5.476858e+09 NaN  0.010092   0.0  0.0  DY010321200101         房地产   \n",
       "4  5.639878e+09 NaN  0.018884   0.0  0.0  DY010321200101         房地产   \n",
       "\n",
       "  LEVEL2_NAME LEVEL3_NAME  \n",
       "0          银行          银行  \n",
       "1       房地产开发        住宅开发  \n",
       "2        生物制品        生物制品  \n",
       "3       房地产开发        住宅开发  \n",
       "4       房地产开发        住宅开发  "
      ]
     },
     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data[\"open\"]=data.groupby(\"CODE\", as_index=False).apply(\n",
    "    lambda x: pd.Series(\n",
    "        np.where(pd.isna(x[\"次日涨跌幅\"]), np.nan, x[\"open\"]),\n",
    "        index=x.index\n",
    "    )\n",
    ").reset_index(level=0, drop=True)\n",
    "data.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7570ab1d",
   "metadata": {},
   "source": [
    "> 将当日为st股票的开盘价置空"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "id": "9578ee84",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2010-01-04</td>\n",
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       "      <th>3</th>\n",
       "      <td>2010-01-04</td>\n",
       "      <td>000005</td>\n",
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       "      <td>NaN</td>\n",
       "      <td>0.010092</td>\n",
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       "      <td>0.0</td>\n",
       "      <td>DY010321200101</td>\n",
       "      <td>房地产</td>\n",
       "      <td>房地产开发</td>\n",
       "      <td>住宅开发</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2010-01-04</td>\n",
       "      <td>000006</td>\n",
       "      <td>222.884995</td>\n",
       "      <td>227.494995</td>\n",
       "      <td>222.684998</td>\n",
       "      <td>227.093994</td>\n",
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       "      <td>住宅开发</td>\n",
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      "text/plain": [
       "        DATE    CODE         open         high          low        close  \\\n",
       "0 2010-01-04  000001   978.291016  1014.187988   977.052979  1011.711975   \n",
       "1 2010-01-04  000002  1074.194946  1101.557007  1074.194946  1099.530029   \n",
       "2 2010-01-04  000004          NaN     0.000000     0.000000     0.000000   \n",
       "3 2010-01-04  000005    58.858002    59.448002    58.071999    59.055000   \n",
       "4 2010-01-04  000006   222.884995   227.494995   222.684998   227.093994   \n",
       "\n",
       "             市值  因子     次日涨跌幅  是否停牌   ST         TYPE_ID LEVEL1_NAME  \\\n",
       "0  7.362984e+10 NaN  0.032420   0.0  0.0  DY010321330101        金融服务   \n",
       "1  1.165492e+11 NaN  0.032351   0.0  0.0  DY010321200101         房地产   \n",
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       "4  5.639878e+09 NaN  0.018884   0.0  0.0  DY010321200101         房地产   \n",
       "\n",
       "  LEVEL2_NAME LEVEL3_NAME  \n",
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       "2        生物制品        生物制品  \n",
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       "4       房地产开发        住宅开发  "
      ]
     },
     "execution_count": 38,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data[\"open\"]=data.groupby(\"CODE\", as_index=False).apply(\n",
    "    lambda x: pd.Series(\n",
    "        np.where(pd.isna(x[\"ST\"]), np.nan, x[\"open\"]),\n",
    "        index=x.index\n",
    "    )\n",
    ").reset_index(level=0, drop=True)\n",
    "data.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "cbfb9953",
   "metadata": {},
   "source": [
    "> 计算收益率"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "id": "d2e2690d",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <td>000005</td>\n",
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       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>DY010321200101</td>\n",
       "      <td>房地产</td>\n",
       "      <td>房地产开发</td>\n",
       "      <td>住宅开发</td>\n",
       "      <td>-0.019353</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2010-01-04</td>\n",
       "      <td>000006</td>\n",
       "      <td>222.884995</td>\n",
       "      <td>227.494995</td>\n",
       "      <td>222.684998</td>\n",
       "      <td>227.093994</td>\n",
       "      <td>5.639878e+09</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.018884</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>DY010321200101</td>\n",
       "      <td>房地产</td>\n",
       "      <td>房地产开发</td>\n",
       "      <td>住宅开发</td>\n",
       "      <td>0.002776</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        DATE    CODE         open         high          low        close  \\\n",
       "0 2010-01-04  000001   978.291016  1014.187988   977.052979  1011.711975   \n",
       "1 2010-01-04  000002  1074.194946  1101.557007  1074.194946  1099.530029   \n",
       "2 2010-01-04  000004          NaN     0.000000     0.000000     0.000000   \n",
       "3 2010-01-04  000005    58.858002    59.448002    58.071999    59.055000   \n",
       "4 2010-01-04  000006   222.884995   227.494995   222.684998   227.093994   \n",
       "\n",
       "             市值  因子     次日涨跌幅  是否停牌   ST         TYPE_ID LEVEL1_NAME  \\\n",
       "0  7.362984e+10 NaN  0.032420   0.0  0.0  DY010321330101        金融服务   \n",
       "1  1.165492e+11 NaN  0.032351   0.0  0.0  DY010321200101         房地产   \n",
       "2  8.397668e+08 NaN       NaN   NaN  NaN  DY010321170301        医药生物   \n",
       "3  5.476858e+09 NaN  0.010092   0.0  0.0  DY010321200101         房地产   \n",
       "4  5.639878e+09 NaN  0.018884   0.0  0.0  DY010321200101         房地产   \n",
       "\n",
       "  LEVEL2_NAME LEVEL3_NAME       收益率  \n",
       "0          银行          银行 -0.017167  \n",
       "1       房地产开发        住宅开发  0.000000  \n",
       "2        生物制品        生物制品       NaN  \n",
       "3       房地产开发        住宅开发 -0.019353  \n",
       "4       房地产开发        住宅开发  0.002776  "
      ]
     },
     "execution_count": 39,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data[\"收益率\"]=data.groupby(\"CODE\",as_index=False).apply(lambda x:x[\"open\"].shift(-2)/x[\"open\"].shift(-1)-1).reset_index(level=0,drop=True)\n",
    "data.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "id": "e7fb2847",
   "metadata": {},
   "outputs": [],
   "source": [
    "#将inf值置空\n",
    "data.loc[data[\"收益率\"] == np.inf, \"收益率\"] = np.nan\n",
    "data.loc[data[\"收益率\"] == -np.inf, \"收益率\"] = np.nan"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "260e0853",
   "metadata": {},
   "source": [
    "> 删除上市不满60天的股票的所有数据"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "id": "ffcbd207",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "8713455"
      ]
     },
     "execution_count": 41,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(data)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "id": "e6184616",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "8710109"
      ]
     },
     "execution_count": 42,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(data.groupby(\"CODE\").filter(lambda x: len(x) >= 60))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "372a8397",
   "metadata": {},
   "source": [
    "总共才删掉了三千多条数据"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "id": "32817022",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>DATE</th>\n",
       "      <th>CODE</th>\n",
       "      <th>open</th>\n",
       "      <th>high</th>\n",
       "      <th>low</th>\n",
       "      <th>close</th>\n",
       "      <th>市值</th>\n",
       "      <th>因子</th>\n",
       "      <th>次日涨跌幅</th>\n",
       "      <th>是否停牌</th>\n",
       "      <th>ST</th>\n",
       "      <th>TYPE_ID</th>\n",
       "      <th>LEVEL1_NAME</th>\n",
       "      <th>LEVEL2_NAME</th>\n",
       "      <th>LEVEL3_NAME</th>\n",
       "      <th>收益率</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2010-01-04</td>\n",
       "      <td>000001</td>\n",
       "      <td>978.291016</td>\n",
       "      <td>1014.187988</td>\n",
       "      <td>977.052979</td>\n",
       "      <td>1011.711975</td>\n",
       "      <td>7.362984e+10</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.032420</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>DY010321330101</td>\n",
       "      <td>金融服务</td>\n",
       "      <td>银行</td>\n",
       "      <td>银行</td>\n",
       "      <td>-0.017167</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2010-01-04</td>\n",
       "      <td>000002</td>\n",
       "      <td>1074.194946</td>\n",
       "      <td>1101.557007</td>\n",
       "      <td>1074.194946</td>\n",
       "      <td>1099.530029</td>\n",
       "      <td>1.165492e+11</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.032351</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>DY010321200101</td>\n",
       "      <td>房地产</td>\n",
       "      <td>房地产开发</td>\n",
       "      <td>住宅开发</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2010-01-04</td>\n",
       "      <td>000004</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>8.397668e+08</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>DY010321170301</td>\n",
       "      <td>医药生物</td>\n",
       "      <td>生物制品</td>\n",
       "      <td>生物制品</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2010-01-04</td>\n",
       "      <td>000005</td>\n",
       "      <td>58.858002</td>\n",
       "      <td>59.448002</td>\n",
       "      <td>58.071999</td>\n",
       "      <td>59.055000</td>\n",
       "      <td>5.476858e+09</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.010092</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>DY010321200101</td>\n",
       "      <td>房地产</td>\n",
       "      <td>房地产开发</td>\n",
       "      <td>住宅开发</td>\n",
       "      <td>-0.019353</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2010-01-04</td>\n",
       "      <td>000006</td>\n",
       "      <td>222.884995</td>\n",
       "      <td>227.494995</td>\n",
       "      <td>222.684998</td>\n",
       "      <td>227.093994</td>\n",
       "      <td>5.639878e+09</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.018884</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>DY010321200101</td>\n",
       "      <td>房地产</td>\n",
       "      <td>房地产开发</td>\n",
       "      <td>住宅开发</td>\n",
       "      <td>0.002776</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        DATE    CODE         open         high          low        close  \\\n",
       "0 2010-01-04  000001   978.291016  1014.187988   977.052979  1011.711975   \n",
       "1 2010-01-04  000002  1074.194946  1101.557007  1074.194946  1099.530029   \n",
       "2 2010-01-04  000004          NaN     0.000000     0.000000     0.000000   \n",
       "3 2010-01-04  000005    58.858002    59.448002    58.071999    59.055000   \n",
       "4 2010-01-04  000006   222.884995   227.494995   222.684998   227.093994   \n",
       "\n",
       "             市值  因子     次日涨跌幅  是否停牌   ST         TYPE_ID LEVEL1_NAME  \\\n",
       "0  7.362984e+10 NaN  0.032420   0.0  0.0  DY010321330101        金融服务   \n",
       "1  1.165492e+11 NaN  0.032351   0.0  0.0  DY010321200101         房地产   \n",
       "2  8.397668e+08 NaN       NaN   NaN  NaN  DY010321170301        医药生物   \n",
       "3  5.476858e+09 NaN  0.010092   0.0  0.0  DY010321200101         房地产   \n",
       "4  5.639878e+09 NaN  0.018884   0.0  0.0  DY010321200101         房地产   \n",
       "\n",
       "  LEVEL2_NAME LEVEL3_NAME       收益率  \n",
       "0          银行          银行 -0.017167  \n",
       "1       房地产开发        住宅开发  0.000000  \n",
       "2        生物制品        生物制品       NaN  \n",
       "3       房地产开发        住宅开发 -0.019353  \n",
       "4       房地产开发        住宅开发  0.002776  "
      ]
     },
     "execution_count": 43,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data=data.groupby(\"CODE\").filter(lambda x: len(x) >= 60)\n",
    "data.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8ddb1fc2",
   "metadata": {},
   "source": [
    "> 删除掉因子、涨跌幅、ST、停牌、open列为空的值，并且删除掉涨跌幅、ST、停牌、open列"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "id": "da9e28ca",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "8710109"
      ]
     },
     "execution_count": 44,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(data)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "id": "a26c3d82",
   "metadata": {},
   "outputs": [],
   "source": [
    "data=data.dropna(how=\"any\",axis=0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "id": "a73e5562",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "7445940"
      ]
     },
     "execution_count": 46,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(data)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "da727649",
   "metadata": {},
   "source": [
    "这次删掉了12万条数据"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "id": "e7f8fe8d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
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       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>DATE</th>\n",
       "      <th>CODE</th>\n",
       "      <th>open</th>\n",
       "      <th>high</th>\n",
       "      <th>low</th>\n",
       "      <th>close</th>\n",
       "      <th>市值</th>\n",
       "      <th>因子</th>\n",
       "      <th>次日涨跌幅</th>\n",
       "      <th>是否停牌</th>\n",
       "      <th>ST</th>\n",
       "      <th>TYPE_ID</th>\n",
       "      <th>LEVEL1_NAME</th>\n",
       "      <th>LEVEL2_NAME</th>\n",
       "      <th>LEVEL3_NAME</th>\n",
       "      <th>收益率</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>8497</th>\n",
       "      <td>2010-01-11</td>\n",
       "      <td>000001</td>\n",
       "      <td>932.492004</td>\n",
       "      <td>977.052979</td>\n",
       "      <td>919.288025</td>\n",
       "      <td>969.627014</td>\n",
       "      <td>7.018281e+10</td>\n",
       "      <td>-0.041598</td>\n",
       "      <td>0.041206</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>DY010321330101</td>\n",
       "      <td>金融服务</td>\n",
       "      <td>银行</td>\n",
       "      <td>银行</td>\n",
       "      <td>-0.066370</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8498</th>\n",
       "      <td>2010-01-11</td>\n",
       "      <td>000002</td>\n",
       "      <td>1031.633057</td>\n",
       "      <td>1074.194946</td>\n",
       "      <td>1021.499023</td>\n",
       "      <td>1066.088013</td>\n",
       "      <td>1.119312e+11</td>\n",
       "      <td>-0.030415</td>\n",
       "      <td>0.038499</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>DY010321200101</td>\n",
       "      <td>房地产</td>\n",
       "      <td>房地产开发</td>\n",
       "      <td>住宅开发</td>\n",
       "      <td>-0.024296</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8500</th>\n",
       "      <td>2010-01-11</td>\n",
       "      <td>000005</td>\n",
       "      <td>57.188000</td>\n",
       "      <td>58.563000</td>\n",
       "      <td>56.598000</td>\n",
       "      <td>57.973999</td>\n",
       "      <td>5.321422e+09</td>\n",
       "      <td>-0.018305</td>\n",
       "      <td>0.017248</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>DY010321200101</td>\n",
       "      <td>房地产</td>\n",
       "      <td>房地产开发</td>\n",
       "      <td>住宅开发</td>\n",
       "      <td>-0.014676</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8501</th>\n",
       "      <td>2010-01-11</td>\n",
       "      <td>000006</td>\n",
       "      <td>214.667007</td>\n",
       "      <td>224.087997</td>\n",
       "      <td>213.865005</td>\n",
       "      <td>224.087997</td>\n",
       "      <td>5.431933e+09</td>\n",
       "      <td>-0.013237</td>\n",
       "      <td>0.028521</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>DY010321200101</td>\n",
       "      <td>房地产</td>\n",
       "      <td>房地产开发</td>\n",
       "      <td>住宅开发</td>\n",
       "      <td>-0.032202</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8504</th>\n",
       "      <td>2010-01-11</td>\n",
       "      <td>000009</td>\n",
       "      <td>48.404999</td>\n",
       "      <td>50.464001</td>\n",
       "      <td>48.011002</td>\n",
       "      <td>49.763000</td>\n",
       "      <td>1.205279e+10</td>\n",
       "      <td>0.032727</td>\n",
       "      <td>0.026189</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>DY010321200101</td>\n",
       "      <td>房地产</td>\n",
       "      <td>房地产开发</td>\n",
       "      <td>住宅开发</td>\n",
       "      <td>-0.052950</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "           DATE    CODE         open         high          low        close  \\\n",
       "8497 2010-01-11  000001   932.492004   977.052979   919.288025   969.627014   \n",
       "8498 2010-01-11  000002  1031.633057  1074.194946  1021.499023  1066.088013   \n",
       "8500 2010-01-11  000005    57.188000    58.563000    56.598000    57.973999   \n",
       "8501 2010-01-11  000006   214.667007   224.087997   213.865005   224.087997   \n",
       "8504 2010-01-11  000009    48.404999    50.464001    48.011002    49.763000   \n",
       "\n",
       "                市值        因子     次日涨跌幅  是否停牌   ST         TYPE_ID LEVEL1_NAME  \\\n",
       "8497  7.018281e+10 -0.041598  0.041206   0.0  0.0  DY010321330101        金融服务   \n",
       "8498  1.119312e+11 -0.030415  0.038499   0.0  0.0  DY010321200101         房地产   \n",
       "8500  5.321422e+09 -0.018305  0.017248   0.0  0.0  DY010321200101         房地产   \n",
       "8501  5.431933e+09 -0.013237  0.028521   0.0  0.0  DY010321200101         房地产   \n",
       "8504  1.205279e+10  0.032727  0.026189   0.0  0.0  DY010321200101         房地产   \n",
       "\n",
       "     LEVEL2_NAME LEVEL3_NAME       收益率  \n",
       "8497          银行          银行 -0.066370  \n",
       "8498       房地产开发        住宅开发 -0.024296  \n",
       "8500       房地产开发        住宅开发 -0.014676  \n",
       "8501       房地产开发        住宅开发 -0.032202  \n",
       "8504       房地产开发        住宅开发 -0.052950  "
      ]
     },
     "execution_count": 47,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "id": "160af887",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th>DATE</th>\n",
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       "      <th>open</th>\n",
       "      <th>high</th>\n",
       "      <th>low</th>\n",
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       "      <th>LEVEL3_NAME</th>\n",
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       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
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       "      <th>8497</th>\n",
       "      <td>2010-01-11</td>\n",
       "      <td>000001</td>\n",
       "      <td>932.492004</td>\n",
       "      <td>977.052979</td>\n",
       "      <td>919.288025</td>\n",
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       "      <td>7.018281e+10</td>\n",
       "      <td>-0.041598</td>\n",
       "      <td>DY010321330101</td>\n",
       "      <td>金融服务</td>\n",
       "      <td>银行</td>\n",
       "      <td>银行</td>\n",
       "      <td>-0.066370</td>\n",
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       "    <tr>\n",
       "      <th>8498</th>\n",
       "      <td>2010-01-11</td>\n",
       "      <td>000002</td>\n",
       "      <td>1031.633057</td>\n",
       "      <td>1074.194946</td>\n",
       "      <td>1021.499023</td>\n",
       "      <td>1066.088013</td>\n",
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       "      <td>住宅开发</td>\n",
       "      <td>-0.024296</td>\n",
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       "    <tr>\n",
       "      <th>8500</th>\n",
       "      <td>2010-01-11</td>\n",
       "      <td>000005</td>\n",
       "      <td>57.188000</td>\n",
       "      <td>58.563000</td>\n",
       "      <td>56.598000</td>\n",
       "      <td>57.973999</td>\n",
       "      <td>5.321422e+09</td>\n",
       "      <td>-0.018305</td>\n",
       "      <td>DY010321200101</td>\n",
       "      <td>房地产</td>\n",
       "      <td>房地产开发</td>\n",
       "      <td>住宅开发</td>\n",
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       "    <tr>\n",
       "      <th>8501</th>\n",
       "      <td>2010-01-11</td>\n",
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       "      <td>住宅开发</td>\n",
       "      <td>-0.032202</td>\n",
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       "    <tr>\n",
       "      <th>8504</th>\n",
       "      <td>2010-01-11</td>\n",
       "      <td>000009</td>\n",
       "      <td>48.404999</td>\n",
       "      <td>50.464001</td>\n",
       "      <td>48.011002</td>\n",
       "      <td>49.763000</td>\n",
       "      <td>1.205279e+10</td>\n",
       "      <td>0.032727</td>\n",
       "      <td>DY010321200101</td>\n",
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       "      <td>房地产开发</td>\n",
       "      <td>住宅开发</td>\n",
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       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "           DATE    CODE         open         high          low        close  \\\n",
       "8497 2010-01-11  000001   932.492004   977.052979   919.288025   969.627014   \n",
       "8498 2010-01-11  000002  1031.633057  1074.194946  1021.499023  1066.088013   \n",
       "8500 2010-01-11  000005    57.188000    58.563000    56.598000    57.973999   \n",
       "8501 2010-01-11  000006   214.667007   224.087997   213.865005   224.087997   \n",
       "8504 2010-01-11  000009    48.404999    50.464001    48.011002    49.763000   \n",
       "\n",
       "                市值        因子         TYPE_ID LEVEL1_NAME LEVEL2_NAME  \\\n",
       "8497  7.018281e+10 -0.041598  DY010321330101        金融服务          银行   \n",
       "8498  1.119312e+11 -0.030415  DY010321200101         房地产       房地产开发   \n",
       "8500  5.321422e+09 -0.018305  DY010321200101         房地产       房地产开发   \n",
       "8501  5.431933e+09 -0.013237  DY010321200101         房地产       房地产开发   \n",
       "8504  1.205279e+10  0.032727  DY010321200101         房地产       房地产开发   \n",
       "\n",
       "     LEVEL3_NAME       收益率  \n",
       "8497          银行 -0.066370  \n",
       "8498        住宅开发 -0.024296  \n",
       "8500        住宅开发 -0.014676  \n",
       "8501        住宅开发 -0.032202  \n",
       "8504        住宅开发 -0.052950  "
      ]
     },
     "execution_count": 48,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data=data.drop([\"次日涨跌幅\",\"次日涨跌幅\",\"ST\",\"是否停牌\"],axis=1)\n",
    "data.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "id": "739abc01",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th>8498</th>\n",
       "      <td>2010-01-11</td>\n",
       "      <td>000002</td>\n",
       "      <td>1031.633057</td>\n",
       "      <td>1074.194946</td>\n",
       "      <td>1021.499023</td>\n",
       "      <td>1066.088013</td>\n",
       "      <td>1.119312e+11</td>\n",
       "      <td>-0.030415</td>\n",
       "      <td>-0.024296</td>\n",
       "      <td>DY010321200101</td>\n",
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       "      <td>住宅开发</td>\n",
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       "    <tr>\n",
       "      <th>8500</th>\n",
       "      <td>2010-01-11</td>\n",
       "      <td>000005</td>\n",
       "      <td>57.188000</td>\n",
       "      <td>58.563000</td>\n",
       "      <td>56.598000</td>\n",
       "      <td>57.973999</td>\n",
       "      <td>5.321422e+09</td>\n",
       "      <td>-0.018305</td>\n",
       "      <td>-0.014676</td>\n",
       "      <td>DY010321200101</td>\n",
       "      <td>房地产</td>\n",
       "      <td>房地产开发</td>\n",
       "      <td>住宅开发</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8501</th>\n",
       "      <td>2010-01-11</td>\n",
       "      <td>000006</td>\n",
       "      <td>214.667007</td>\n",
       "      <td>224.087997</td>\n",
       "      <td>213.865005</td>\n",
       "      <td>224.087997</td>\n",
       "      <td>5.431933e+09</td>\n",
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       "      <td>-0.032202</td>\n",
       "      <td>DY010321200101</td>\n",
       "      <td>房地产</td>\n",
       "      <td>房地产开发</td>\n",
       "      <td>住宅开发</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8504</th>\n",
       "      <td>2010-01-11</td>\n",
       "      <td>000009</td>\n",
       "      <td>48.404999</td>\n",
       "      <td>50.464001</td>\n",
       "      <td>48.011002</td>\n",
       "      <td>49.763000</td>\n",
       "      <td>1.205279e+10</td>\n",
       "      <td>0.032727</td>\n",
       "      <td>-0.052950</td>\n",
       "      <td>DY010321200101</td>\n",
       "      <td>房地产</td>\n",
       "      <td>房地产开发</td>\n",
       "      <td>住宅开发</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "           DATE    CODE         open         high          low        close  \\\n",
       "8497 2010-01-11  000001   932.492004   977.052979   919.288025   969.627014   \n",
       "8498 2010-01-11  000002  1031.633057  1074.194946  1021.499023  1066.088013   \n",
       "8500 2010-01-11  000005    57.188000    58.563000    56.598000    57.973999   \n",
       "8501 2010-01-11  000006   214.667007   224.087997   213.865005   224.087997   \n",
       "8504 2010-01-11  000009    48.404999    50.464001    48.011002    49.763000   \n",
       "\n",
       "                市值        因子       收益率         TYPE_ID LEVEL1_NAME  \\\n",
       "8497  7.018281e+10 -0.041598 -0.066370  DY010321330101        金融服务   \n",
       "8498  1.119312e+11 -0.030415 -0.024296  DY010321200101         房地产   \n",
       "8500  5.321422e+09 -0.018305 -0.014676  DY010321200101         房地产   \n",
       "8501  5.431933e+09 -0.013237 -0.032202  DY010321200101         房地产   \n",
       "8504  1.205279e+10  0.032727 -0.052950  DY010321200101         房地产   \n",
       "\n",
       "     LEVEL2_NAME LEVEL3_NAME  \n",
       "8497          银行          银行  \n",
       "8498       房地产开发        住宅开发  \n",
       "8500       房地产开发        住宅开发  \n",
       "8501       房地产开发        住宅开发  \n",
       "8504       房地产开发        住宅开发  "
      ]
     },
     "execution_count": 49,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data=data[[\"DATE\",\"CODE\",\"open\",\"high\",\"low\",\"close\",\"市值\",\"因子\",\"收益率\",\"TYPE_ID\",\"LEVEL1_NAME\",\"LEVEL2_NAME\",\"LEVEL3_NAME\"]]\n",
    "data.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "id": "1e1a4ff0",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th>收益率</th>\n",
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       "      <th>0</th>\n",
       "      <td>2010-01-11</td>\n",
       "      <td>000001</td>\n",
       "      <td>932.492004</td>\n",
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       "      <td>919.288025</td>\n",
       "      <td>969.627014</td>\n",
       "      <td>7.018281e+10</td>\n",
       "      <td>-0.041598</td>\n",
       "      <td>-0.066370</td>\n",
       "      <td>DY010321330101</td>\n",
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       "      <td>银行</td>\n",
       "      <td>银行</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2010-01-11</td>\n",
       "      <td>000002</td>\n",
       "      <td>1031.633057</td>\n",
       "      <td>1074.194946</td>\n",
       "      <td>1021.499023</td>\n",
       "      <td>1066.088013</td>\n",
       "      <td>1.119312e+11</td>\n",
       "      <td>-0.030415</td>\n",
       "      <td>-0.024296</td>\n",
       "      <td>DY010321200101</td>\n",
       "      <td>房地产</td>\n",
       "      <td>房地产开发</td>\n",
       "      <td>住宅开发</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2010-01-11</td>\n",
       "      <td>000005</td>\n",
       "      <td>57.188000</td>\n",
       "      <td>58.563000</td>\n",
       "      <td>56.598000</td>\n",
       "      <td>57.973999</td>\n",
       "      <td>5.321422e+09</td>\n",
       "      <td>-0.018305</td>\n",
       "      <td>-0.014676</td>\n",
       "      <td>DY010321200101</td>\n",
       "      <td>房地产</td>\n",
       "      <td>房地产开发</td>\n",
       "      <td>住宅开发</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2010-01-11</td>\n",
       "      <td>000006</td>\n",
       "      <td>214.667007</td>\n",
       "      <td>224.087997</td>\n",
       "      <td>213.865005</td>\n",
       "      <td>224.087997</td>\n",
       "      <td>5.431933e+09</td>\n",
       "      <td>-0.013237</td>\n",
       "      <td>-0.032202</td>\n",
       "      <td>DY010321200101</td>\n",
       "      <td>房地产</td>\n",
       "      <td>房地产开发</td>\n",
       "      <td>住宅开发</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2010-01-11</td>\n",
       "      <td>000009</td>\n",
       "      <td>48.404999</td>\n",
       "      <td>50.464001</td>\n",
       "      <td>48.011002</td>\n",
       "      <td>49.763000</td>\n",
       "      <td>1.205279e+10</td>\n",
       "      <td>0.032727</td>\n",
       "      <td>-0.052950</td>\n",
       "      <td>DY010321200101</td>\n",
       "      <td>房地产</td>\n",
       "      <td>房地产开发</td>\n",
       "      <td>住宅开发</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        DATE    CODE         open         high          low        close  \\\n",
       "0 2010-01-11  000001   932.492004   977.052979   919.288025   969.627014   \n",
       "1 2010-01-11  000002  1031.633057  1074.194946  1021.499023  1066.088013   \n",
       "2 2010-01-11  000005    57.188000    58.563000    56.598000    57.973999   \n",
       "3 2010-01-11  000006   214.667007   224.087997   213.865005   224.087997   \n",
       "4 2010-01-11  000009    48.404999    50.464001    48.011002    49.763000   \n",
       "\n",
       "             市值        因子       收益率         TYPE_ID LEVEL1_NAME LEVEL2_NAME  \\\n",
       "0  7.018281e+10 -0.041598 -0.066370  DY010321330101        金融服务          银行   \n",
       "1  1.119312e+11 -0.030415 -0.024296  DY010321200101         房地产       房地产开发   \n",
       "2  5.321422e+09 -0.018305 -0.014676  DY010321200101         房地产       房地产开发   \n",
       "3  5.431933e+09 -0.013237 -0.032202  DY010321200101         房地产       房地产开发   \n",
       "4  1.205279e+10  0.032727 -0.052950  DY010321200101         房地产       房地产开发   \n",
       "\n",
       "  LEVEL3_NAME  \n",
       "0          银行  \n",
       "1        住宅开发  \n",
       "2        住宅开发  \n",
       "3        住宅开发  \n",
       "4        住宅开发  "
      ]
     },
     "execution_count": 50,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.reset_index(drop=True,inplace=True)\n",
    "data.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0d94ad1f",
   "metadata": {},
   "source": [
    "## **四、检查数据有没有极端值**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "id": "a67d4215",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>DATE</th>\n",
       "      <th>open</th>\n",
       "      <th>high</th>\n",
       "      <th>low</th>\n",
       "      <th>close</th>\n",
       "      <th>市值</th>\n",
       "      <th>因子</th>\n",
       "      <th>收益率</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>7445940</td>\n",
       "      <td>7.445940e+06</td>\n",
       "      <td>7.445940e+06</td>\n",
       "      <td>7.445940e+06</td>\n",
       "      <td>7.445940e+06</td>\n",
       "      <td>7.445940e+06</td>\n",
       "      <td>7.445940e+06</td>\n",
       "      <td>7.445940e+06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>2016-12-16 04:23:16.625595648</td>\n",
       "      <td>1.355934e+02</td>\n",
       "      <td>1.381218e+02</td>\n",
       "      <td>1.330027e+02</td>\n",
       "      <td>1.354023e+02</td>\n",
       "      <td>1.758711e+10</td>\n",
       "      <td>2.435895e-03</td>\n",
       "      <td>5.312415e-04</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>2010-01-11 00:00:00</td>\n",
       "      <td>1.355000e+00</td>\n",
       "      <td>1.376000e+00</td>\n",
       "      <td>1.345000e+00</td>\n",
       "      <td>1.366000e+00</td>\n",
       "      <td>4.778105e+08</td>\n",
       "      <td>-6.453789e-01</td>\n",
       "      <td>-1.896037e-01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>2014-01-15 00:00:00</td>\n",
       "      <td>2.113500e+01</td>\n",
       "      <td>2.151100e+01</td>\n",
       "      <td>2.074900e+01</td>\n",
       "      <td>2.110600e+01</td>\n",
       "      <td>3.226608e+09</td>\n",
       "      <td>-3.291925e-02</td>\n",
       "      <td>-1.341511e-02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>2017-07-11 00:00:00</td>\n",
       "      <td>3.731900e+01</td>\n",
       "      <td>3.801200e+01</td>\n",
       "      <td>3.660200e+01</td>\n",
       "      <td>3.726400e+01</td>\n",
       "      <td>5.600000e+09</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>2019-12-02 00:00:00</td>\n",
       "      <td>6.903300e+01</td>\n",
       "      <td>7.038000e+01</td>\n",
       "      <td>6.765200e+01</td>\n",
       "      <td>6.893000e+01</td>\n",
       "      <td>1.162103e+10</td>\n",
       "      <td>3.362142e-02</td>\n",
       "      <td>1.344192e-02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>2021-12-28 00:00:00</td>\n",
       "      <td>3.331197e+05</td>\n",
       "      <td>3.478956e+05</td>\n",
       "      <td>3.182335e+05</td>\n",
       "      <td>3.224237e+05</td>\n",
       "      <td>3.267370e+12</td>\n",
       "      <td>1.257324e+00</td>\n",
       "      <td>2.004895e-01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>NaN</td>\n",
       "      <td>1.941198e+03</td>\n",
       "      <td>1.981072e+03</td>\n",
       "      <td>1.899647e+03</td>\n",
       "      <td>1.937249e+03</td>\n",
       "      <td>7.644919e+10</td>\n",
       "      <td>6.757342e-02</td>\n",
       "      <td>2.585736e-02</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                DATE          open          high  \\\n",
       "count                        7445940  7.445940e+06  7.445940e+06   \n",
       "mean   2016-12-16 04:23:16.625595648  1.355934e+02  1.381218e+02   \n",
       "min              2010-01-11 00:00:00  1.355000e+00  1.376000e+00   \n",
       "25%              2014-01-15 00:00:00  2.113500e+01  2.151100e+01   \n",
       "50%              2017-07-11 00:00:00  3.731900e+01  3.801200e+01   \n",
       "75%              2019-12-02 00:00:00  6.903300e+01  7.038000e+01   \n",
       "max              2021-12-28 00:00:00  3.331197e+05  3.478956e+05   \n",
       "std                              NaN  1.941198e+03  1.981072e+03   \n",
       "\n",
       "                low         close            市值            因子           收益率  \n",
       "count  7.445940e+06  7.445940e+06  7.445940e+06  7.445940e+06  7.445940e+06  \n",
       "mean   1.330027e+02  1.354023e+02  1.758711e+10  2.435895e-03  5.312415e-04  \n",
       "min    1.345000e+00  1.366000e+00  4.778105e+08 -6.453789e-01 -1.896037e-01  \n",
       "25%    2.074900e+01  2.110600e+01  3.226608e+09 -3.291925e-02 -1.341511e-02  \n",
       "50%    3.660200e+01  3.726400e+01  5.600000e+09  0.000000e+00  0.000000e+00  \n",
       "75%    6.765200e+01  6.893000e+01  1.162103e+10  3.362142e-02  1.344192e-02  \n",
       "max    3.182335e+05  3.224237e+05  3.267370e+12  1.257324e+00  2.004895e-01  \n",
       "std    1.899647e+03  1.937249e+03  7.644919e+10  6.757342e-02  2.585736e-02  "
      ]
     },
     "execution_count": 51,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "id": "32d70770",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 7445940 entries, 0 to 7445939\n",
      "Data columns (total 13 columns):\n",
      " #   Column       Dtype         \n",
      "---  ------       -----         \n",
      " 0   DATE         datetime64[ns]\n",
      " 1   CODE         object        \n",
      " 2   open         float32       \n",
      " 3   high         float32       \n",
      " 4   low          float32       \n",
      " 5   close        float32       \n",
      " 6   市值           float32       \n",
      " 7   因子           float32       \n",
      " 8   收益率          float32       \n",
      " 9   TYPE_ID      object        \n",
      " 10  LEVEL1_NAME  object        \n",
      " 11  LEVEL2_NAME  object        \n",
      " 12  LEVEL3_NAME  object        \n",
      "dtypes: datetime64[ns](1), float32(7), object(5)\n",
      "memory usage: 539.7+ MB\n"
     ]
    }
   ],
   "source": [
    "data.info()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "581256a9",
   "metadata": {},
   "source": [
    "数据的分布看起来都很合理，继续操作"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1404d8dd",
   "metadata": {},
   "source": [
    "## **五、合并数据（这一步我先跳过，合并完之后我操作着不是很顺手**"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "eb014034",
   "metadata": {},
   "source": [
    "## **六、因子值标准化**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "id": "1d930249",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>DATE</th>\n",
       "      <th>CODE</th>\n",
       "      <th>open</th>\n",
       "      <th>high</th>\n",
       "      <th>low</th>\n",
       "      <th>close</th>\n",
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       "      <th>因子</th>\n",
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       "      <th>TYPE_ID</th>\n",
       "      <th>LEVEL1_NAME</th>\n",
       "      <th>LEVEL2_NAME</th>\n",
       "      <th>LEVEL3_NAME</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2010-01-11</td>\n",
       "      <td>000001</td>\n",
       "      <td>932.492004</td>\n",
       "      <td>977.052979</td>\n",
       "      <td>919.288025</td>\n",
       "      <td>969.627014</td>\n",
       "      <td>7.018281e+10</td>\n",
       "      <td>-0.041598</td>\n",
       "      <td>-0.066370</td>\n",
       "      <td>DY010321330101</td>\n",
       "      <td>金融服务</td>\n",
       "      <td>银行</td>\n",
       "      <td>银行</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2010-01-11</td>\n",
       "      <td>000002</td>\n",
       "      <td>1031.633057</td>\n",
       "      <td>1074.194946</td>\n",
       "      <td>1021.499023</td>\n",
       "      <td>1066.088013</td>\n",
       "      <td>1.119312e+11</td>\n",
       "      <td>-0.030415</td>\n",
       "      <td>-0.024296</td>\n",
       "      <td>DY010321200101</td>\n",
       "      <td>房地产</td>\n",
       "      <td>房地产开发</td>\n",
       "      <td>住宅开发</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2010-01-11</td>\n",
       "      <td>000005</td>\n",
       "      <td>57.188000</td>\n",
       "      <td>58.563000</td>\n",
       "      <td>56.598000</td>\n",
       "      <td>57.973999</td>\n",
       "      <td>5.321422e+09</td>\n",
       "      <td>-0.018305</td>\n",
       "      <td>-0.014676</td>\n",
       "      <td>DY010321200101</td>\n",
       "      <td>房地产</td>\n",
       "      <td>房地产开发</td>\n",
       "      <td>住宅开发</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2010-01-11</td>\n",
       "      <td>000006</td>\n",
       "      <td>214.667007</td>\n",
       "      <td>224.087997</td>\n",
       "      <td>213.865005</td>\n",
       "      <td>224.087997</td>\n",
       "      <td>5.431933e+09</td>\n",
       "      <td>-0.013237</td>\n",
       "      <td>-0.032202</td>\n",
       "      <td>DY010321200101</td>\n",
       "      <td>房地产</td>\n",
       "      <td>房地产开发</td>\n",
       "      <td>住宅开发</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2010-01-11</td>\n",
       "      <td>000009</td>\n",
       "      <td>48.404999</td>\n",
       "      <td>50.464001</td>\n",
       "      <td>48.011002</td>\n",
       "      <td>49.763000</td>\n",
       "      <td>1.205279e+10</td>\n",
       "      <td>0.032727</td>\n",
       "      <td>-0.052950</td>\n",
       "      <td>DY010321200101</td>\n",
       "      <td>房地产</td>\n",
       "      <td>房地产开发</td>\n",
       "      <td>住宅开发</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        DATE    CODE         open         high          low        close  \\\n",
       "0 2010-01-11  000001   932.492004   977.052979   919.288025   969.627014   \n",
       "1 2010-01-11  000002  1031.633057  1074.194946  1021.499023  1066.088013   \n",
       "2 2010-01-11  000005    57.188000    58.563000    56.598000    57.973999   \n",
       "3 2010-01-11  000006   214.667007   224.087997   213.865005   224.087997   \n",
       "4 2010-01-11  000009    48.404999    50.464001    48.011002    49.763000   \n",
       "\n",
       "             市值        因子       收益率         TYPE_ID LEVEL1_NAME LEVEL2_NAME  \\\n",
       "0  7.018281e+10 -0.041598 -0.066370  DY010321330101        金融服务          银行   \n",
       "1  1.119312e+11 -0.030415 -0.024296  DY010321200101         房地产       房地产开发   \n",
       "2  5.321422e+09 -0.018305 -0.014676  DY010321200101         房地产       房地产开发   \n",
       "3  5.431933e+09 -0.013237 -0.032202  DY010321200101         房地产       房地产开发   \n",
       "4  1.205279e+10  0.032727 -0.052950  DY010321200101         房地产       房地产开发   \n",
       "\n",
       "  LEVEL3_NAME  \n",
       "0          银行  \n",
       "1        住宅开发  \n",
       "2        住宅开发  \n",
       "3        住宅开发  \n",
       "4        住宅开发  "
      ]
     },
     "execution_count": 53,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.head()"
   ]
  },
  {
   "attachments": {
    "image.png": {
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"
    }
   },
   "cell_type": "markdown",
   "id": "4f0aa7e9",
   "metadata": {},
   "source": [
    "![image.png](attachment:image.png)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "id": "d9435c96",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Z-Score标准化\n",
    "# 按日期（DATE）分组，对每个日期截面的“因子”列做 Z-Score 标准化\n",
    "def zscore_standardize(df):\n",
    "    def zscore_group(group):\n",
    "        mean = group['因子'].mean()\n",
    "        std = group['因子'].std()\n",
    "        group['因子_ZScore'] = (group['因子'] - mean) / std\n",
    "        return group\n",
    "    return df.groupby('DATE').apply(zscore_group).reset_index(level=0,drop=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "id": "df5a6b82",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>DATE</th>\n",
       "      <th>CODE</th>\n",
       "      <th>open</th>\n",
       "      <th>high</th>\n",
       "      <th>low</th>\n",
       "      <th>close</th>\n",
       "      <th>市值</th>\n",
       "      <th>因子</th>\n",
       "      <th>收益率</th>\n",
       "      <th>TYPE_ID</th>\n",
       "      <th>LEVEL1_NAME</th>\n",
       "      <th>LEVEL2_NAME</th>\n",
       "      <th>LEVEL3_NAME</th>\n",
       "      <th>因子_ZScore</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2010-01-11</td>\n",
       "      <td>000001</td>\n",
       "      <td>932.492004</td>\n",
       "      <td>977.052979</td>\n",
       "      <td>919.288025</td>\n",
       "      <td>969.627014</td>\n",
       "      <td>7.018281e+10</td>\n",
       "      <td>-0.041598</td>\n",
       "      <td>-0.066370</td>\n",
       "      <td>DY010321330101</td>\n",
       "      <td>金融服务</td>\n",
       "      <td>银行</td>\n",
       "      <td>银行</td>\n",
       "      <td>-0.814615</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2010-01-11</td>\n",
       "      <td>000002</td>\n",
       "      <td>1031.633057</td>\n",
       "      <td>1074.194946</td>\n",
       "      <td>1021.499023</td>\n",
       "      <td>1066.088013</td>\n",
       "      <td>1.119312e+11</td>\n",
       "      <td>-0.030415</td>\n",
       "      <td>-0.024296</td>\n",
       "      <td>DY010321200101</td>\n",
       "      <td>房地产</td>\n",
       "      <td>房地产开发</td>\n",
       "      <td>住宅开发</td>\n",
       "      <td>-0.601393</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2010-01-11</td>\n",
       "      <td>000005</td>\n",
       "      <td>57.188000</td>\n",
       "      <td>58.563000</td>\n",
       "      <td>56.598000</td>\n",
       "      <td>57.973999</td>\n",
       "      <td>5.321422e+09</td>\n",
       "      <td>-0.018305</td>\n",
       "      <td>-0.014676</td>\n",
       "      <td>DY010321200101</td>\n",
       "      <td>房地产</td>\n",
       "      <td>房地产开发</td>\n",
       "      <td>住宅开发</td>\n",
       "      <td>-0.370499</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2010-01-11</td>\n",
       "      <td>000006</td>\n",
       "      <td>214.667007</td>\n",
       "      <td>224.087997</td>\n",
       "      <td>213.865005</td>\n",
       "      <td>224.087997</td>\n",
       "      <td>5.431933e+09</td>\n",
       "      <td>-0.013237</td>\n",
       "      <td>-0.032202</td>\n",
       "      <td>DY010321200101</td>\n",
       "      <td>房地产</td>\n",
       "      <td>房地产开发</td>\n",
       "      <td>住宅开发</td>\n",
       "      <td>-0.273866</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2010-01-11</td>\n",
       "      <td>000009</td>\n",
       "      <td>48.404999</td>\n",
       "      <td>50.464001</td>\n",
       "      <td>48.011002</td>\n",
       "      <td>49.763000</td>\n",
       "      <td>1.205279e+10</td>\n",
       "      <td>0.032727</td>\n",
       "      <td>-0.052950</td>\n",
       "      <td>DY010321200101</td>\n",
       "      <td>房地产</td>\n",
       "      <td>房地产开发</td>\n",
       "      <td>住宅开发</td>\n",
       "      <td>0.602516</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        DATE    CODE         open         high          low        close  \\\n",
       "0 2010-01-11  000001   932.492004   977.052979   919.288025   969.627014   \n",
       "1 2010-01-11  000002  1031.633057  1074.194946  1021.499023  1066.088013   \n",
       "2 2010-01-11  000005    57.188000    58.563000    56.598000    57.973999   \n",
       "3 2010-01-11  000006   214.667007   224.087997   213.865005   224.087997   \n",
       "4 2010-01-11  000009    48.404999    50.464001    48.011002    49.763000   \n",
       "\n",
       "             市值        因子       收益率         TYPE_ID LEVEL1_NAME LEVEL2_NAME  \\\n",
       "0  7.018281e+10 -0.041598 -0.066370  DY010321330101        金融服务          银行   \n",
       "1  1.119312e+11 -0.030415 -0.024296  DY010321200101         房地产       房地产开发   \n",
       "2  5.321422e+09 -0.018305 -0.014676  DY010321200101         房地产       房地产开发   \n",
       "3  5.431933e+09 -0.013237 -0.032202  DY010321200101         房地产       房地产开发   \n",
       "4  1.205279e+10  0.032727 -0.052950  DY010321200101         房地产       房地产开发   \n",
       "\n",
       "  LEVEL3_NAME  因子_ZScore  \n",
       "0          银行  -0.814615  \n",
       "1        住宅开发  -0.601393  \n",
       "2        住宅开发  -0.370499  \n",
       "3        住宅开发  -0.273866  \n",
       "4        住宅开发   0.602516  "
      ]
     },
     "execution_count": 55,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 调用函数\n",
    "data=zscore_standardize(data)\n",
    "data.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "55988ad7",
   "metadata": {},
   "source": [
    "## **七、因子值中性化**"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "774ef00c",
   "metadata": {},
   "source": [
    "> 先对因子做行业中性化（回归行业虚拟变量 ），再对行业中性化后的残差做市值中性化（回归市值 ）"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "id": "7a05d3f1",
   "metadata": {},
   "outputs": [],
   "source": [
    "def two_step_neutralize(df, factor_col, mkt_col, industry_col):\n",
    "    \"\"\"\n",
    "    两步法：先行业中性化，再市值中性化\n",
    "    :param df: 原始数据DataFrame\n",
    "    :param factor_col: 要中性化的因子列名（如\"因子\" ）\n",
    "    :param mkt_col: 市值列名（如\"市值\" ）\n",
    "    :param industry_col: 行业分类列名（如\"LEVEL2_NAME\" ）\n",
    "    :return: 新增\"中性化因子_两步法\"列的DataFrame\n",
    "    \"\"\"\n",
    "    # 第一步：行业中性化（回归行业虚拟变量 ）\n",
    "    def industry_step(group):\n",
    "        formula = f\"{factor_col} ~ C({industry_col})\"\n",
    "        y, X = dmatrices(formula, data=group, return_type='dataframe')\n",
    "        model = sm.OLS(y, X)\n",
    "        try:\n",
    "            results = model.fit()\n",
    "            return results.resid\n",
    "        except:\n",
    "            return pd.Series([0]*len(group), index=group.index)\n",
    "    \n",
    "    df[\"行业中性化因子\"] = df.groupby(industry_col).apply(industry_step).reset_index(level=0, drop=True)\n",
    "    \n",
    "    # 第二步：市值中性化（对行业中性化后的因子，回归市值 ）\n",
    "    def mkt_step(group):\n",
    "        formula = \"行业中性化因子 ~ \" + mkt_col\n",
    "        y, X = dmatrices(formula, data=group, return_type='dataframe')\n",
    "        model = sm.OLS(y, X)\n",
    "        try:\n",
    "            results = model.fit()\n",
    "            return results.resid\n",
    "        except:\n",
    "            return pd.Series([0]*len(group), index=group.index)\n",
    "    \n",
    "    df[\"中性化因子_两步法\"] = df.groupby(industry_col).apply(mkt_step).reset_index(level=0, drop=True)\n",
    "    return df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "id": "ecde8c92",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>DATE</th>\n",
       "      <th>CODE</th>\n",
       "      <th>open</th>\n",
       "      <th>high</th>\n",
       "      <th>low</th>\n",
       "      <th>close</th>\n",
       "      <th>市值</th>\n",
       "      <th>因子</th>\n",
       "      <th>收益率</th>\n",
       "      <th>TYPE_ID</th>\n",
       "      <th>LEVEL1_NAME</th>\n",
       "      <th>LEVEL2_NAME</th>\n",
       "      <th>LEVEL3_NAME</th>\n",
       "      <th>因子_ZScore</th>\n",
       "      <th>行业中性化因子</th>\n",
       "      <th>中性化因子_两步法</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2010-01-11</td>\n",
       "      <td>000001</td>\n",
       "      <td>932.492004</td>\n",
       "      <td>977.052979</td>\n",
       "      <td>919.288025</td>\n",
       "      <td>969.627014</td>\n",
       "      <td>7.018281e+10</td>\n",
       "      <td>-0.041598</td>\n",
       "      <td>-0.066370</td>\n",
       "      <td>DY010321330101</td>\n",
       "      <td>金融服务</td>\n",
       "      <td>银行</td>\n",
       "      <td>银行</td>\n",
       "      <td>-0.814615</td>\n",
       "      <td>-0.795526</td>\n",
       "      <td>-0.790467</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2010-01-11</td>\n",
       "      <td>000002</td>\n",
       "      <td>1031.633057</td>\n",
       "      <td>1074.194946</td>\n",
       "      <td>1021.499023</td>\n",
       "      <td>1066.088013</td>\n",
       "      <td>1.119312e+11</td>\n",
       "      <td>-0.030415</td>\n",
       "      <td>-0.024296</td>\n",
       "      <td>DY010321200101</td>\n",
       "      <td>房地产</td>\n",
       "      <td>房地产开发</td>\n",
       "      <td>住宅开发</td>\n",
       "      <td>-0.601393</td>\n",
       "      <td>-0.581622</td>\n",
       "      <td>-0.632511</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2010-01-11</td>\n",
       "      <td>000005</td>\n",
       "      <td>57.188000</td>\n",
       "      <td>58.563000</td>\n",
       "      <td>56.598000</td>\n",
       "      <td>57.973999</td>\n",
       "      <td>5.321422e+09</td>\n",
       "      <td>-0.018305</td>\n",
       "      <td>-0.014676</td>\n",
       "      <td>DY010321200101</td>\n",
       "      <td>房地产</td>\n",
       "      <td>房地产开发</td>\n",
       "      <td>住宅开发</td>\n",
       "      <td>-0.370499</td>\n",
       "      <td>-0.350728</td>\n",
       "      <td>-0.346565</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2010-01-11</td>\n",
       "      <td>000006</td>\n",
       "      <td>214.667007</td>\n",
       "      <td>224.087997</td>\n",
       "      <td>213.865005</td>\n",
       "      <td>224.087997</td>\n",
       "      <td>5.431933e+09</td>\n",
       "      <td>-0.013237</td>\n",
       "      <td>-0.032202</td>\n",
       "      <td>DY010321200101</td>\n",
       "      <td>房地产</td>\n",
       "      <td>房地产开发</td>\n",
       "      <td>住宅开发</td>\n",
       "      <td>-0.273866</td>\n",
       "      <td>-0.254095</td>\n",
       "      <td>-0.249989</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2010-01-11</td>\n",
       "      <td>000009</td>\n",
       "      <td>48.404999</td>\n",
       "      <td>50.464001</td>\n",
       "      <td>48.011002</td>\n",
       "      <td>49.763000</td>\n",
       "      <td>1.205279e+10</td>\n",
       "      <td>0.032727</td>\n",
       "      <td>-0.052950</td>\n",
       "      <td>DY010321200101</td>\n",
       "      <td>房地产</td>\n",
       "      <td>房地产开发</td>\n",
       "      <td>住宅开发</td>\n",
       "      <td>0.602516</td>\n",
       "      <td>0.622287</td>\n",
       "      <td>0.622974</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        DATE    CODE         open         high          low        close  \\\n",
       "0 2010-01-11  000001   932.492004   977.052979   919.288025   969.627014   \n",
       "1 2010-01-11  000002  1031.633057  1074.194946  1021.499023  1066.088013   \n",
       "2 2010-01-11  000005    57.188000    58.563000    56.598000    57.973999   \n",
       "3 2010-01-11  000006   214.667007   224.087997   213.865005   224.087997   \n",
       "4 2010-01-11  000009    48.404999    50.464001    48.011002    49.763000   \n",
       "\n",
       "             市值        因子       收益率         TYPE_ID LEVEL1_NAME LEVEL2_NAME  \\\n",
       "0  7.018281e+10 -0.041598 -0.066370  DY010321330101        金融服务          银行   \n",
       "1  1.119312e+11 -0.030415 -0.024296  DY010321200101         房地产       房地产开发   \n",
       "2  5.321422e+09 -0.018305 -0.014676  DY010321200101         房地产       房地产开发   \n",
       "3  5.431933e+09 -0.013237 -0.032202  DY010321200101         房地产       房地产开发   \n",
       "4  1.205279e+10  0.032727 -0.052950  DY010321200101         房地产       房地产开发   \n",
       "\n",
       "  LEVEL3_NAME  因子_ZScore   行业中性化因子  中性化因子_两步法  \n",
       "0          银行  -0.814615 -0.795526  -0.790467  \n",
       "1        住宅开发  -0.601393 -0.581622  -0.632511  \n",
       "2        住宅开发  -0.370499 -0.350728  -0.346565  \n",
       "3        住宅开发  -0.273866 -0.254095  -0.249989  \n",
       "4        住宅开发   0.602516  0.622287   0.622974  "
      ]
     },
     "execution_count": 57,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 调用两步法函数\n",
    "data=two_step_neutralize(data, \"因子_ZScore\", \"市值\", \"LEVEL2_NAME\")\n",
    "data.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "id": "afd0fff3",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['DATE', 'CODE', 'open', 'high', 'low', 'close', '市值', '因子', '收益率',\n",
       "       'TYPE_ID', 'LEVEL1_NAME', 'LEVEL2_NAME', 'LEVEL3_NAME', '因子_ZScore',\n",
       "       '行业中性化因子', '中性化因子_两步法'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 58,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "id": "eaac2c06",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
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       "\n",
       "    .dataframe tbody tr th {\n",
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       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>DATE</th>\n",
       "      <th>CODE</th>\n",
       "      <th>open</th>\n",
       "      <th>high</th>\n",
       "      <th>low</th>\n",
       "      <th>close</th>\n",
       "      <th>市值</th>\n",
       "      <th>因子</th>\n",
       "      <th>因子_ZScore</th>\n",
       "      <th>中性化因子_两步法</th>\n",
       "      <th>收益率</th>\n",
       "      <th>TYPE_ID</th>\n",
       "      <th>LEVEL1_NAME</th>\n",
       "      <th>LEVEL2_NAME</th>\n",
       "      <th>LEVEL3_NAME</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2010-01-11</td>\n",
       "      <td>000001</td>\n",
       "      <td>932.492004</td>\n",
       "      <td>977.052979</td>\n",
       "      <td>919.288025</td>\n",
       "      <td>969.627014</td>\n",
       "      <td>7.018281e+10</td>\n",
       "      <td>-0.041598</td>\n",
       "      <td>-0.814615</td>\n",
       "      <td>-0.790467</td>\n",
       "      <td>-0.066370</td>\n",
       "      <td>DY010321330101</td>\n",
       "      <td>金融服务</td>\n",
       "      <td>银行</td>\n",
       "      <td>银行</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2010-01-11</td>\n",
       "      <td>000002</td>\n",
       "      <td>1031.633057</td>\n",
       "      <td>1074.194946</td>\n",
       "      <td>1021.499023</td>\n",
       "      <td>1066.088013</td>\n",
       "      <td>1.119312e+11</td>\n",
       "      <td>-0.030415</td>\n",
       "      <td>-0.601393</td>\n",
       "      <td>-0.632511</td>\n",
       "      <td>-0.024296</td>\n",
       "      <td>DY010321200101</td>\n",
       "      <td>房地产</td>\n",
       "      <td>房地产开发</td>\n",
       "      <td>住宅开发</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2010-01-11</td>\n",
       "      <td>000005</td>\n",
       "      <td>57.188000</td>\n",
       "      <td>58.563000</td>\n",
       "      <td>56.598000</td>\n",
       "      <td>57.973999</td>\n",
       "      <td>5.321422e+09</td>\n",
       "      <td>-0.018305</td>\n",
       "      <td>-0.370499</td>\n",
       "      <td>-0.346565</td>\n",
       "      <td>-0.014676</td>\n",
       "      <td>DY010321200101</td>\n",
       "      <td>房地产</td>\n",
       "      <td>房地产开发</td>\n",
       "      <td>住宅开发</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2010-01-11</td>\n",
       "      <td>000006</td>\n",
       "      <td>214.667007</td>\n",
       "      <td>224.087997</td>\n",
       "      <td>213.865005</td>\n",
       "      <td>224.087997</td>\n",
       "      <td>5.431933e+09</td>\n",
       "      <td>-0.013237</td>\n",
       "      <td>-0.273866</td>\n",
       "      <td>-0.249989</td>\n",
       "      <td>-0.032202</td>\n",
       "      <td>DY010321200101</td>\n",
       "      <td>房地产</td>\n",
       "      <td>房地产开发</td>\n",
       "      <td>住宅开发</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2010-01-11</td>\n",
       "      <td>000009</td>\n",
       "      <td>48.404999</td>\n",
       "      <td>50.464001</td>\n",
       "      <td>48.011002</td>\n",
       "      <td>49.763000</td>\n",
       "      <td>1.205279e+10</td>\n",
       "      <td>0.032727</td>\n",
       "      <td>0.602516</td>\n",
       "      <td>0.622974</td>\n",
       "      <td>-0.052950</td>\n",
       "      <td>DY010321200101</td>\n",
       "      <td>房地产</td>\n",
       "      <td>房地产开发</td>\n",
       "      <td>住宅开发</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        DATE    CODE         open         high          low        close  \\\n",
       "0 2010-01-11  000001   932.492004   977.052979   919.288025   969.627014   \n",
       "1 2010-01-11  000002  1031.633057  1074.194946  1021.499023  1066.088013   \n",
       "2 2010-01-11  000005    57.188000    58.563000    56.598000    57.973999   \n",
       "3 2010-01-11  000006   214.667007   224.087997   213.865005   224.087997   \n",
       "4 2010-01-11  000009    48.404999    50.464001    48.011002    49.763000   \n",
       "\n",
       "             市值        因子  因子_ZScore  中性化因子_两步法       收益率         TYPE_ID  \\\n",
       "0  7.018281e+10 -0.041598  -0.814615  -0.790467 -0.066370  DY010321330101   \n",
       "1  1.119312e+11 -0.030415  -0.601393  -0.632511 -0.024296  DY010321200101   \n",
       "2  5.321422e+09 -0.018305  -0.370499  -0.346565 -0.014676  DY010321200101   \n",
       "3  5.431933e+09 -0.013237  -0.273866  -0.249989 -0.032202  DY010321200101   \n",
       "4  1.205279e+10  0.032727   0.602516   0.622974 -0.052950  DY010321200101   \n",
       "\n",
       "  LEVEL1_NAME LEVEL2_NAME LEVEL3_NAME  \n",
       "0        金融服务          银行          银行  \n",
       "1         房地产       房地产开发        住宅开发  \n",
       "2         房地产       房地产开发        住宅开发  \n",
       "3         房地产       房地产开发        住宅开发  \n",
       "4         房地产       房地产开发        住宅开发  "
      ]
     },
     "execution_count": 59,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#调整列顺序，更美观\n",
    "data=data[['DATE', 'CODE', 'open', 'high', 'low', 'close', '市值', '因子', '因子_ZScore', '中性化因子_两步法' , '收益率',\n",
    "       'TYPE_ID', 'LEVEL1_NAME', 'LEVEL2_NAME', 'LEVEL3_NAME']]\n",
    "data.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ca521088",
   "metadata": {},
   "source": [
    "## **八、计算两个因子的IC值**"
   ]
  },
  {
   "attachments": {
    "image.png": {
     "image/png": 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aF5uUlBQuXbzI8RPHmTRpss437amTJ7l//z7lyzvj6OjI8WPH1NKqbt2+hbGxMaVKlUKpVHLf25syjo74PfLjStoFB+DXXw/w668H5N9V+vXrl2EUn11Xr1xh8y+/AODi4kLfvj9n+02U3uvXr5gxfQa7dmlfKGJjY7l27RrXrl0jIjycxUuWys+hkZERnX/qzOk/TnP50iU2b95Mnbp1dfZW/X8SExPzxTn8n0uSJB48eMDCBQvw9X2Iu3tFJk2enGlPWnj4O3nOUoECBSlSpKjeIOVrzFF4GxYGgLf3n3h762+IZZWqR8XV1RVXV1fNYi0nThzn+LFjODg60KtXr8/6H9q2a0v4u3COHfudokWLaQUciQkJcqpG0++bki9/vm9+Ybp16xY+Pg+oVasWR48e1RukpudQujR169VLHY1Zvpy4DHoLz587p3lKHmGKjo4mJjaGxR66UzsK2doyZsxYLC0t6dq1G127qqeGaJIkiZMnTzB71izatm1H7969Pyvt6MyZM1qjF6NHj1L7XRXEGRsb4+fnx820a+SC+X9dR3RJHbkojJWlJR07diIpKQl/f38K2drStWtXrPP+NRoRnxDPwV9/VSt3d3fH29tbrjNo8GCmTZue4SIjfzdJkvj92DGOHz+mWfTN6epd/RIuLi7cv/8AExMTvL295bSf8uXLM2jwYPnaFR0dLY/UWFhYMH/+PIxz5SLg2V9ziyZOGI+FxkRu1byIY8d+lxvpCfHxvHz5EtLSgQcNHICJqSl2xYrRslUr+baa8xfSSz+/RZf0E31VTExNsSlQgPB372jcuAlRHz6wbGnqaGt0TDT79u6T69oUKICJqSnr161Ldw/aKd+izfX5Xrx4wfJly7DJb0OPHj0xNTUlIiKCFcuXkTdvXjp26kRCQgIJCQmkpKRw8Ndf8fX1Zfr0GeTIkYPY2FjMzc2/2uIBegOFxMRELqQblqtduzZ2dnbMm7+AWbMzHvrMTI4cOfRebG/dvsWSxak9adlx67b6GzIjMTExHDlyhCWLPXj69CkAzs7OjJ8wgbZt2+lsKAcFBTF71iy5ARz1IYpFHh7Y2Nio1cssjer0qVOcPnVK/v3RI18aNGyols/5d/nw4QNbtmyRhwa7deuepRxbfW7evMmwoUPUhrcdHR1xc3PH2dmZkJA3eHt7qw33pVe4cBF69+4tj0Tt2LGD7+p/RyFbW82qwhdKSEhg3759rF+3FoVCQe/effi5X78srZZy69Ytnj8PYPiIEVnuXf8SSclJAPTu3Ye69bKfo6vJwsLib3ncKvnz56d79x4EBgbi5eWlM+CIioriwYP7AHTp2lVr9OBrS98T7uXlpTU8rc/QYcOpW68enz4pCXwZKI+SfI7Aly8JTGsUaapVq5bcEyZJEhfOnycoOJguXbrovHbcvXuXFStW0Kx5c3788UeMjIxQKpV8+PCBfPnyaTWk/fz8uHfvLj/+2FHn/XXp0lVrlaH0wRxpI2uXLl5EoVAwdtx4ypcvr1Zf5cSJ4xz89Vc5raFgoUL06duXy1cu4+/vTwEbG3r16q01mfnWrVta5ekDhQI2BTJMxcnIxUuXtSZda6Yn6Uor+vPPP2nXri1hoaEUsrWlTBn19NAnT57guf6vBmSHDj/Qt2/fbH/eomOiWbhggTyHyLZQIZ2vU3q6Hq8+mTWmSWunZGWeR3BwMD4+DyBdZ5gmXdc81byIuLg4nVka6e+rcZMmWj3Dn+vFi+dMmTJZ87Ts8OFD8uIxuoS/e8eK5dqpprpSvlVEmyvr3r19y4rly3j+PICFCxdRsmRJFAoFixd7yG3ytm10T7wfMWI4ZDCX8XPpDRRCQ9XTjhwdHcmRIwfm5uapeXlRqUuoZZdT+fIZNkY0X9Sv6d3bt/zyyy9s3bpVLdeuY8dOdOnSBTMzMy6cP4+/vz9KpRJUebx373Lx4gW1XLtTp05S/7vv6Natm1YUnF2vX72Se6UAFi3ykCfzvnr9ijmzZ/Py5Utat25Dj569vlpP431vb86cSc2rLFu2LI2bNNG6oGaVv78/48aOkS8yjRo3ZtKkyVSvXl1teFKSJAIDA/W+xt/V/44GDRty4fx5Lpw/z81bN2nbtp1mta8mLi6ON2/eUKJEia/2vP7TvX79isWLF3P+3DnsS5Rg7vARNGzUKEvvY1UD08XFRa1hExMTw9KlS7SG6TObo5C+51ifkLRJ7mXLlf2qq6b8l927e5ebN25QvXoNps+YjqWl9neyr68vAwf0p3//AfRISztUfUbs7e05dPiwxi3+IkkSkiRpvd6fQ6FQcP3Gdfbv28ezZ08ZN2682lyA+/fvs3DBAmrVqsWoUaOxsrJKy+/9jZUrVvBTl6706dMHY2NjJEnCy8uLhQsXEP7uHSVKlFTL5Vdp1ry52upQaARzAM+ePeP8hfM0bNSI9u3b630P37uXmgahb4TjXXg427Zt1RpReBUcrFbvn+D58wD5M+7o6Iit7V/BlEKhYNXKFfI1wM6uOEOHDdMKSNIvXqJv6de9e/fIQYKFhQWdOnXWSmPTlJU5Fd/CzZs35cnAgjrR5sqelJQUDh06xIULFxg1egx169UjIiKCCxfO06lTZ0xNTbl9+zZDhgyhQIGCvHv3lrVr19KzZ09KlixFUlISB/b/NfrztegNFC5evKiWd6eSlJTEpo0b5GW/suvipcsZTu5r2qwZdWpnf8WAq9eu6m18qihTlFy8dFHtDQtw4MB+DhzQnzOcnrW1Nf3692fwoME6e7onT5nC5ClTSExMZN++fUycMJ7IdHmTM2bM5Oeff8YqTx5y5cqFJEmsXbNGfq6dnZ1p1rw5ZcqUAeD69evyUGThwra4uLjoveBkR1JSEidPnZQ/iA0bNaJUqVKa1bIkPj6eNatXyf9D3759mTtvvs6JfQYGBpQoUYJBgwdrFkFab1vdOnXliXAnjh+nceMmmV4kPkdoaAiTJ03mzp3b9OrVm+EjRvxtXwj/CykpKVy7ehWPxR4EvnxJ/fr1GTN2HCVKlNCsqpeqgenm5qb2ZZ2SkkJYaCgvXr7EPi2nFCBnzhw468h/T0lJITAo9XOYUU9ZcnIyMdHRAORN15D6X4lNW30mo++wzOiaa5GYkEBoWBi2OtbKf/LEn5YtdPfUfY6YmBiOHT+GQqEgISGBnDlz6hzBUH3mjHPl0lmuT3x8PL/++itvXr9m5KhRWukCwcFBLFywgO+bNqVJk++1yjWZm5szduw4rCyt2LhxAzHR0UydNo2CBQtx7epV5sydQ6VKlRgwYACSJBEVFcXly5dYtHAhlStXpk2b1hgbGxMfH8/27dvZumUzNgUKsHTZ8izNfdAlOSmJUydPEhoSwoTxE/QGCZIkkZLWANInLDSUpUuWaJ7O1OvXr9RSJ9L7FnsNSZKEv/9fI0hO5crJn0mlUskGT082b94slw8YMICqVavKv6uk7wF2cXHh+6ZN1QKFt2Fh7E83h6dz587U0hHMfUuay5umt2nTJvn8sOHDiXyfen0vXbo0+/YfoEKFCmojFhYWFpw4eUrvPgolS5Zi3rzUVJzXb17LKT3pU9IsrazIZfxXr3v6tCRNycnJPMxg0rq5uTmNGjfWPK0mNiZGbRTEzc2N/Bo9+Zp0fUeINlf2GBoa0qx5c3KbmdGpUyeMjIy4desms2fNYsWKlVSpUoWHPg8pX94Ze3t7AgMDMTUxxdGxDO7u7iQkJHD+vHbK55fSGZZ9+PCBUydPap7+W1SrWo2x48Zl+6hWVfeHML18+fLj5uameTpLrK2tGTtuHLfv3GH27Dk637CkfZl6e3vTuXMn+vf7We0NC3Dj5g06dGhP586duHfvHm/evOb3tInEpPXivUs3yScy8q8l8woWzHz4Navev4/g/v2/eseqVKmic/gvK27euMG+falRbM2aNZkwcZLOICErDAwM1C4u9+/f582bN2p1vpYPH6IIDFTlg74gISFBs8pX4+3tjXN5J62jdq2aeHl5cWD/fipXqqhV7lzeSS3d4EsEBwezcuVKwt+9Y+iw4SxesjRbQUJcXBxnz53NcL+GOnXqsHrNWjZs3JThsXrNWupkYQlBpVJJQmLq65JZg/JbS0pKYteuXbRp3YodO3YQr7HSW1Z5e//JmtWrWL5sqXysW7eWF8+fa1aFtAZ7pUqVqVWrltpRrlzGc0n0uXf3Ll5pKQ2RHyKJjU3d6E2TatS4cGHd33WakpKSuHL5Mr179cJj0UK8rnvh6+urWQ3/x/4Ev3rFlMmT+fHHH9i7d4+82Zw+pqamDBw0iBEjR/H02TMe+z0mNDQET09PQkNCOH7sGI0bNaJ2rZrUrlWTKZMn06BhQ+bMnSdPIL508SJbt2ymeo0aeHp6Urt27c8eQfX29ubXXw/Q5PvvqaqnAUhaCm/E+wjN01/F5s2bady4kc7j8CH9qSNfYvjwEYSEhhESGsa8+Qvk65Gfnx+bN6fOdQNo1ao1PXr0yHCyqz6HDx+W2x+FbG3p1PknnZ99U1NT1qxdR2JS8hcfWU1Z0vTH6dOcv5DaqeXi4oqdnZ1mFUqUKJFhClO1an+1ecqX/6tTRZVyNnbcOPr37495uo3XVGlJ586e1TouX7qk1e5Ir1Wr1pw4cTLDY+EiD7XbjB03TquO5jF4yBC12yDaXJ/F3t6enj17YmJiwvv37zl96pTa90yKlLoASlRUFHFxcaRIKSgUCqKiooiJjiY5ORnSRviioqJ0Hh8/ftT4qxnT+Sm+7+3NhbQ3vyZjY2P69R9Ax46dNIuyRNfkm/RmzZqZYb7ZlzA2NqZmzZrkyJGDAjYFKFu2LGZmZtgVL06uXMacPXuOObNnq0W/1tbWDB06jB49e/Dq1WsOHTzEgIEDdX5xPX36lLlz5rA/3dBP167dqFChAhMnTgCQl1ADOHniBKVLl9YatgwKCpQbUS+ev5DP2xXX/hL6XMHBr/BOW42gdOnSODvr3kwoM5IkcfPmTXlkom3bdjq/LLPDwdGBGjVqcOPGDXx8fHj69Emm75vPUaZMGQYNHszlS5fo2q273l7Br0Hf8qWqZUktrazUeuLT+9wATh83Nzc6d04dxsyOO7dv65yg+i0lJCTw5vVrbGxsuHjhgtYKGtlhZWVJixYts/1/q0R9+ICpiSmfPn3CY9FCTp44wYiRI6lWrZrO100fXfmj6Tdc06Rv5awTJ44zYfx4tXOZiQgP5/ffj2JpZUWT77/nyOHDRERE6Px8Bb9K3VXW0iLjz0VKSgqPHz9m/bq1XLp0CTMzM/r2/ZmevXrp7DBo8v331KxVi8OHD7PBcz3z5s5l9+7ddO3albZt2+l9fYyNjenZsycNGzaUA9zhI0YAUKxYUYxzGrNz5062bNlM167dGD5ihNpIZJPvv6dAwYKUL1/+iy/+VapWZcfOXRgZGZGUlMTz588/e0RW18TUrOTQfwldk2vTT6QFWLF8Obt27VKro9KieQu1hmG5cuXo3bsPU6ZMxs6uOKPHjKFAwYKkpKRgYGCQrYCsV+/eFChYgGVLl9KwUSNq1FBfOvb69euftZ9AVqiWYc2d+6+VsDLi7FyBQraFOH7sODVq1JDTqt+/fy8vwpBVHz58+Gav95cqUkR9aeasEm2uzydJEhcvXuD27dssXLhIbp88e/qUzp06qtUdOKC/2u8dO3Vi+7ZtbNny1whfekOHDWfgwIGap/XSChQUCgV79uz+6mvf/lO0a9debSfF+Ph4Tp48wbKlS9U2X3J0dGTQoMF06twZKysr9u7dw/hx44iMjOTV61fMnj1HKx3G0sKC8Ihw+fdx48czYcJEtRUgRo4aRZHCRViwYD6RkZFab1jSJoQplUqUSiWvXqderPnKazEHBwfJr3HhIkV0bqSXFXFxcTx7lrpzooWFBdVr1MjWRUGXvHmtKVmylLziVvoP7tdkZGREx46dPjvozQ59y5eqls6sW7cuQ4cN0zvEGRgYqHlKXlo1o9Sd9FS9D0plCjExqek8mTE0NMTMzIwPHz5w8OCvFC5SBLPc+tPArl69qnMugiZV6lHJLI5ohIeH6/3Sy6qOnTrRsuVfK4dkV4GCBRk9ZgwNGjZk5YoV+Po+pN/PfWndpg1Dhw6lcOEimjf5x1F8VJCUlESrlq2oVbs2Z/74g0ePHmnlkScnJxMWGopd8eIULqL7/5IkiadPn7J58y+cPHECgPr16zN4yFDKlSuX4feAubk5PXr0oGXLlmzfto19+/bKAUPfvn1p2rSZzoaBsbEx9vb23Lx5k/iPH/muQQMMDAxQKBRs2riR/fv3MWnyZH78sWPqwgk3b9Kvf39MTU159eoVL148l1MMvoSBgQFlypQhJOQN48aOJTExkbnz5mW61KsuKZlsuPYt6Jpcqyn9iLOmWjXVOz1y5MjBoMGDCQx8Se06dahRowZKpZLly5bx+PFjhg4bhqura4bfCwqFgu3btuFcoQIdOvxAy5atUCqVnzUq8aVMTEzkhVtSlEoWeSySl87s2bMnM2fNIlcuE/n/GTt2LCkpKfJrGBMTI38v63p9VSwsLOR0V80OWh8fH3r36imvCJRe6dKlmTptGkV0fOfExsWycMECnanjWRWfzR7njIg21+cJDQ3h6G9Hqf/dd/KSpwB2xYtnaY6Ck5MTo0aPITk5Ga9r14iOiabp903JZWKCQwYbSOqi9Qn09fXlyJEjmqdl33qOQt++fenc+SfN05nat2+vWn5kZmJiYti7dy8bN3iqDY/Xrl2bsWPHUf+77+QL1adPn/j0SSkP6axZvZrkpCTmzV+ARbrhQFV+fcCzAObMnUOD7xqwaeNGtQ3qrCytGD5iBG3atmX2rFlUqFCBJ0/8OXnqFJYWFjx9+pT79+/z4cMHkpOT5C/rihUrftHOqZpUuyAD5M+Xn9wZNP4ykpSUxLvw1GG7zIZYsypnzpxYWJjLv4dHhKNUKvU2ov/NQkJCePLEnw4/dMjwIqqLamnVrK5Yo/IMaN6smeZpncqUKYvH4sVcvnyZu3fvMn3GjNTh29evNat+E7lz52bwkKH83E+9xyQ7Xrx4zpzZszVPfxYDAwNq1KiBm5ubnO/++9Gj+Pj4MGjQIBo3bpLpPBfVvIv0qW4xMdEolSkYGWXvPZBdxYvbM2XqVHLmzEkOoxw4OZXHz++RvM+JSmxsLM+ePaVI4cI6v6/DQkNZsXIFx4+lXpArVarMwEGDsj26Ym1tzajRo+nUuRNr1qzh96NHmTZ1Knfv3mXKlKlaPbshIW/kejVq1MDZ2Zmk5CQWL17M8+fP1eYdRESEs3v3LszMzfnpp584fOgQW7ZsZvv27Zm+Vk+fPtFqqCvi4oiNjVP7brK1LUyLli2YOWMGK5YvY/qMmTqfLzMzM73PS2YbrumjWko8fQ97VjYm+1bMzMxYuMgDExMTDAwMeP78Ofv378PHx4ddu3Yya9Zsxk9I7eXVdOXyZSZNmsjdu3epWbMm27bvoHjxzHcb1/x/9e33k37OgeYIjq4RCgMDA3l0IDAwkFvp1ttPSEjE1DQ3efPm1VopSpeMXl/V6lP6Omjv3r1Ls2ZN6datO02bNZXP586dm0qVKuscCXz//j1WOuYLZDTvIjOaz48+/fr1U1v2PL3/epsrO5RKJQd/PYi39584ODqozWczNTHN0hyF+t99h4mJCQkJCbx795Y3r19/9op6WoFC3rx5KVGiRIZv/G8pv43NZ23+k9lEG9INkW/Zspk9u3fLuWzW1tZ06dqVPn36Uq5cOa0v9ISEBFq3bk1CfDwjR6YOdW/YsIFPnz6pTdo1MDCg808/0aVrV4oXL87169eZP38esbGxWl9OxYsXZ2PaB9bPzw9XN/fU1Wg8PPDx8eHly5fExcbK6UHlyjlRoEAB+TF9qfQ5wfnyWeu9YP4vmJiYqO2Q+CEykqSkJJ1fPv9mSqWSP9NWRFm7Zg1mZma0bNkqywGRoaEhhWxtdaY06aJKc8qRIwdlypQlZ06tj78WcwsLjI1zYmRkRLPmzalRo6a8iosuderU0Uqr0UW1MVhmAYexsXGW9jrIiKpH0iSXSZaf28yYmpoyYMAA6tSpw8IFC/D2/pMJ48dzptEZxo0bR9GixTRvIjty+DBH9KwYlNXX8kvY2aU2wJKTkylXrhynTp0kMDCQChX+Sj8MCgrCx8eHDh1+ULswq+TJmxdLC0ucnSvQu3dvKlWuTI4cOYiJ+bzN93LnNmPixEl06PADO3fuoHXrNmpBQnh4OLt27mTfvr0A9O37M51/6sztO7fx9PQkn3U+FixYSLFixXjy5AmxsbFYW+ejdp06bNzgSaFCBRkxciQ1atZk5YoVTBg/Hq82XnpHgjIKLNO/RgYGBrRo0RL/x/7s27eXQoVs1TZCUilatFiGq/39nZydndmwcRMlSpQgPDyc5ctSU3waNmykWRUA5adPrFy1Ul623MLCggouulNVzc1Tg6hPnz6xa9dOuR1RtmxZWrRsqXVtVclrbS1fk65fv86ypUuYv2ChVg+ypuioKG7evIGFeep7NH1vcfrJ3klJSbx9m9qh9fHjR+7duyuv3vQ43QRtTZIkcf78ebXe+f3795GQkMCSpdmfgK7PjevXM+ygffX6FdLfvEnt1yDaXJ/n5s2b7N6tO+0vozkKSYmJJCcnZ3s54sxotRRsbGwoUrQo5ubm2NgUkLeKVvnWcxQWLVzIooULNU9/scTERKZNm8rKFSvUztvZFeeHH38gIjyc8Wk5wqpVAzQnxWhSjWCo3rgfPnzAY9FCObc3Ijxc7iGIiopmxIjhWh8IVa5nhQoV5OGysNBQLl+6RGxcrHx7V1dX+Uv4n+rjx48kJiZqnhb0eP78OWfOnsHZuQKmpqZMmTyZoMAgOVUiM5aWlsyapb9Bo0mV5pQ/fz4WeSzOVs9CnTp1qF+/vlYP77+BatKxpZXVV/0CNTAwoHz58nhu2MDmX35h9+5dnD93Dj8/P6ZOmUq9+vU1bwKgc4dnzTX6STfykP7CkN7nTqZWyZkzJ1WrVmXHju1cvnQJJycnef8Br2vXUCgUVK1aVedzZmJiwvARI8iRIwcJCQmfNbKlSTV3Y9my5XLaUmJiIlu3bmXnju1ER0fTuk0bBg8eTJEiRTl/7hwT03qoA1++5KfO+q9JGzZswMHBkRo1auDk5MQvmzaxdesWLl+6xOzZc2jYSL2RnJV9FFRMTU3p07cPT5484ejR33B1c6V58xYZpl6lpyuN5Gukj6SXmJgoT2A0NEzd6fvy5UvMmD6dp0+f4ufnh4uLq9ZKSZIksX//PjakbQgG0LFjRxo00L9zO8CDBw/Yuyc1qCMtbzyjjRydnZ3p168/Y8ak7j6/e/duatSsSadOnTN8Hm/fvk37drqXz968ebPOLIOAgIAsL6MaGhqilv+ucvTob4SGhjBs+HAcHctQoGBBuSwlJYWAZwFqeffVqlXTmhNC2udIcz8jldKlS1OvXj2OHDlCp06d1TofNIOd9GLjYj97+fqvSbS5Ps+LFy9Yu2aNVmeDSlbnKHxNWoGCqakpxe3scGnVmrDQUK1A4d8qV65cODhoBynBwUHyDoSfI/0bV5IkXr1+rXPzlODgIK0lwtDI9XR0LIOLiws+Pj6sWLmChLSGQCFbW2rWqpXhF+b/ipmZGaVKluRs2hewr+9DtZ5JQbe4uDi2bdvK27AwFi5cRMVKlVi+fBkbN24gNCyUMWPG6kxh+F9R5V5ntjLUgf37OZBuacPM/B096B8+ZHzx+VJmZmYMGz6cipUqsXDhAiwtLCmWwYT+zDZcU1Gt+KTrwpAdISFv9G6MVt7ZmRo1anDx4kVatmqFvb09YWGhXL9+nRo1amQ4uqu6iKreE5oB0L27d3j8+DGtWrWWUyHehoWxZ89utYa4ZgM8/YU9V65clHF0pHhxe4YNH66W2uTs7MzoMWMpWLAABQqkNtTy5s1Ljhw5MDUxwTpfPnLmzMmdO3dYumQJQYGBlC5dGisrK0aNHo2LiwsHDuzHwVF7k8ms7KOQXuHCRejTpw8TJ05gxYoV2NuX0LsBmyZdaST60kc+V2xsrFpvu6GhIQ4OjvJzefv2baZOmcK6devUGr1Xr15l2tRpcuOpatWqDB8xMsOe/vj4eLZu2Sxf72rWrEmnzp0zHM0zMDCgU+fOXLlyhaNHfyM2NpalS5bg5uauFbwUKFBAXk70a7O0spIXj1Aqlezbu0/eAFTT7du3mTJ5CitXrqR5ixby+cDAQLp366p2vR89Zoze/YC2bt3KoUMHAahbty4hISEEBASQO3duRo4azZChwyhUqBBPnjyRb5OdYEcl/byLjDzy9aV//35qE9vd3NxY77kh03Sw9JvpijZX9qWkpPDH6dOEhoYwadJkjhzRHnlOP0ch8v17Hj16hH0Je4oVs/v79lEwMTGhWvXqNGvWXGuLbr7RHIX2HTro3PQmvYDnz/FYtBBTU1MmT5lCwbQLg6a4uDi1L7r0KlWqRCFbW51RuCriT79+cPp1jM0tLCjj6Ch/2d2/f5/Zs2cRGxtLQkKiPOmqWNGiNGjYUK1HIX1vgmZvQ/qJWsWLF6dO3br4+PgQnm65rmpVq1E6m5NPMmOTbkjt9Zs3JCQkZKkXW5OJiQnOFVzk34/9foymTZt90VyF+Ph4QkL+WhK1YBZ25fw3USgULF++jN+PHqVz55+oXqMGpqamTJgwEeu81mzcuIHI9++ZOGlytpYv/SfQbCzqo5pgpen161csX76cuK+wmELdevXo2jV191PSVsb5VgwMDKhduza/bPqF2Li4z5rUqo+Liyv9+/fHTKN3687t26xbt1btXHrv37/n9OnTcm+8LjY2NjRr3pzp06bx+9GjDBw0iJMnT+Hj84CJkyZpfVdnRDMASk5O5u3bd7Tv0EFescnb25s9e3arNcQzaoAD1Ktfn7r16mk1NAvZ2tKnTx+1c6qVoBZ5eNCiRUtI+97fsXOnWnqloaEhjZs0of5332X6Xs2qWrVr8+OPHXnw4IHcwFCt2pXeurVr+e3ob/Ja97rWxE+/Fr6qfOSoUXJ5dgUF/bUYQsFChciXLx/W1tZMmjyZoUOGEBsby7Fjv2NsbMySpUuwtS3MmT/+YOjQofK1ys6uOPPmL9BquGs6d+6svFw2QL/+/bO0Ep6NjQ2DBw/m1u1bhIWG4uPjw2IPD5avWKG2Il3p0qUZNXr0F238qovm3hO3bt1i/fr1anUAevToQeEiRVi4YAGurq5UrlxZrVzXHlQH9h+gXr36Oq+LJiapgYmdXXF69OzJqpUr1cqzGnBmJv28C30UCgWHDh1UCxJIa+/89tsRpk+fka3J5aLNlT2GhobUrlMH09y5qVylilag0KJFS/l7jbTv0zFjRrPIw0PejPRbdL7pfMW7dOmqeeqbef/+Pb8dOUKdunWpUqUKSUlJ7NmzR95kqU7duuTNm5cxY0bLb95rV69q5S+GhYayfft2fvnlFwYNGoS7u7vWhaVcuXIcPHiIwoVtyZkjJ4qPH7G3t1eLGtNPbFKtY6zq6QkPD8fnwQNq16lDzVq1SEpK4k3IG2bPniPn8a733MDDhw/p1jV1XeaWLVvh6ekpN8zTl5UtW1Zty/NcuXLRqmUrdmzfrjYM2ax5c51fMF8i/Y6aUR8+EBsb89l/o169enJUfujQQdzc3BgxcuRnL+uZlJTE+7RNbEibjPR3R/bfSvpdkRs0aMDAQYPkAM3U1JT+AwaQM2dO1q5dw9gxY5g6bdpnr0P9v6DZWNQn/QSr9D59UhL4MlBvD3h2uFesBOl2dv47FLK1RXPLtAcPHnD37l2io6KIjHyf4YZrAHt27yZf/nzUrVuXN69fU9y+OFWqVtXqxX337q3a76SliiiVSp488adnj+6QtoSjo6Mpd+7oTmOpX/87GjZqxO7du4iOiebKlSu4u1ekQdqKQv9rmqkD2WVoaKh3DtbXChJIS8sdMHBg6ohGBp0uUVFRar3UsWlr4uujKu/7888oUzLevE0XpVKJn5+f/HsBmwIYGxtjYGDADz/8yOtXr5kyZTIAhw4dJDQ0hKrVqrFj+3Y5FcTCwoI5c+dkuvdJSMgbVq9eLV+/OnT4gWbNmmf5fVS7Th169uwppx/v2rUTd3d3hgwdqnYfX9phqUv6yc+pKzD9tZtw79692bp1K6Rdp4cOHYYkSXTp0lWtYzL83Tt5gn96Z878wbVrV2nVqrVmEWXKlKWQrS3tO7THzU19FEsfCwsLXF1dM9xwLbM0Hk2fPn3iwIED7N69W7MI0gLcsmXL0rnzT1n+TIo2V/Y5OztTvnx5rflewcFBnD2rvjy5agnee/fuERb21/XA3NyMVq1af7VU4ay92hlo2qwZ8+bN13tMnTYtwx6IJ0+esGTJYhp8V5/v6tfj4cOH/P77UaZMmcyUKZN58eI5Dg4OjBk7Vn5jeHp6sn7dOhITU6NKgDt377B4sQfBwUFs375N7YtRxdTUlCpVqpA/vw07d+6kZYvmHD36W5YmCcXGxjJn9iyaN2/G8GFDeR8RwajRo1myZKnaZD+FQsH6dWvlHSxjYmO4dfsWMTExhIS8YdbMmXJZz569tPI2CxQsqDa8V7lyZerryXX+EsWL28sRs6+vL6Gh2VvzOT0HBwcGDvprp+Vp06YyeNAggtJ23k1PkiRevnzJ+nXr9OZYR0REyBuh8RV7VP6X4uPj2bt3DwMHDuT8uXM0+f57pk6dptVja2JiQv8BAxg9ZiyvX79i/Phxf/veBf9LxYoVY+u2bVzzuv7FR48ePSCtocT/cGfn169fsXzZUrZs2Ux4eHiGG669eP6cdevWcuH8ed69C+fDhyjy5smrt6Gryd/fn+vXrwNgZWXF+AkT2bptG9WqV9esKrO2tqZbt+5YWlmxf98+YqKj6dKli85Jvn+3wMBAOrRvr7UJob5Dta/EhPHjtcr0HbNnz8o0pS6rLCwsdAYJ1tZ5v3ifFoXiIyHpNp8sUTJro40xMTE88f8rbaVI0SJyAyJHjhwMGz6cOXPmyuXXr19nxfLlakHC4iVL+eGHHzNs8H/69AlPT085CLKzK87QYcOy1eDKkSMHffv+rLZc78qVK7X2TzEwMCC/jQ316tdX26vDwsKC2rVr06hxY72Hvo6X9B1bZmZm8uZnbdq0pWUr9WWVzc3NmT17jlrbRqlUsnPnTjnv3cLCgu7de2BhYUFsbCzLli7VeU20tS1E5UqV6date5Y710qUKMF6zw1am56dOHGSvXv3UUljlCMziYmJbNywgXFjx8gN5po1a3L69B/yaxEbG8vwYcPwXL8+y3MR/7+3uT5+/PhZG5hlxMDAQGcg9v59pNo1Y/mypezZkxrUHdi/X+38hfPnSUpK0ryLz6b9aLIps52UBw8eojdfV6lUcvbsGfmNWa16dezttXPgDAwMaNOmLd26p/aQWVtbY1OgAE+ePKFvnz54e3tTv/53dOyYmsfr7+/PBs/1OhuikZGRjB83lsmTJxEQEMDPffuya9dOuTGhi1KpZM3q1WzYsAGAbdu20bJlC27duqX1gr5/H0FiYpL8Rr5y+TId2renjKMDdWrX4VjajoADBw5kwMCBaqMewcFBTJkyWW3psLt37zJl8mTevdXuPfwSdnZ2uLikriYTGxv7RatcGRgY0LlzZyZMnCif27VrJ44OpalbpzaTJk1kyeLFjBg+jOrVqlK2jCOPHmnv2KoS+PKlfGFwcXHR+/75UklJSWzZsoXevXpx4fz5LH15fY7ExERWrljBvLlz5V2R582brzdFzsjIiJ49ezJg4CAK2BTA/l+UfpTRDtPpj8qVKuqcy2BkZISlpSV58uT54iN37typO+OGp66zrasB93do0aIlvo/85OP6jZvcvfen/PsDn4dcunyFh76P5HMbNm4iJSWFoKBACtnaZrnnu1ixYpQrW5aGjRqx/8ABevTokaX/265YMRwdUnP18+XPT34bm2/2eciOHDmMsC9hr7Urtb5DtVt1uXJOWmX6Duu81hk2gL9ESkoKKSkpGBoayteKyVOmyDsCnzt/gaVLlxH5IUptp+Co6BjWrffkoe8j+VzLli0ISLd7d0Yra6UXEBDArdt/7ZugmrSukitXLrp07UKbNm3lc+l16dKF9u3bZ5pycuniRdat/SsVrk+fPlStWlWtTlbY2dnRr/9fkzODg4NYt3atWg+riYkJM2fO4syZs5z+44w8RyA2NpaoqChatmjJtq3b5Mbz0aO/s2iRB2XLliU4OFi+H9KW5zx16jSjRqdOpJbP16mDnV1xuvfojrV15svNenl5qaUqNWnyPbNmz6Jd2mTr69evs3TJYrWeawBzcwt69dZuwP5d3oaFMXzYUEaNGik/NgsLCwYNHsx3DRoweswYuT0TGxvLqFEj9XYE6vL/tc2VkJDAkiWLqV2rJte/cCGHrHB3d1e7jly6fIV69epRslQpNmzchM9DX7XrR56vOMfpiwOFL/Hq1St5EoqFhQWtWrbC2Fh3RG1qasr48ePp168fly5foWfPngQHB7F37x6qV6vKuLFjaNykibzN9759+9RyoCVJ4t69e3Ro3w7PdCs4VKhQAWfnClppSukZGRkxeswYli9fIb8ZfXx8aN2qpTyyoWJnV5xfNm/m3p/ezJgxU16KMDIyktdpG3nYFCiAvX0JPioUkO6x9ezRQ966Pr1Dhw7Su09vtclMX8rS0pLq6XoZb1y/rvUFlh1mZmZMmTKVlStXqfXw3Lp1i2VLlzJlymQ8PT0z3MSHtC+IS5f/GpavVq0axYpl7YKYXQEBAezcsZ07d25z6NDBL/r/M5IrVy5+7tePgQMHsWPnLgYMGJBp400VLKxavfp/kiv5udzdKzJ02HBGjR6T4TF02HDc3Stq3vyr+/TpE4qPCuyKF9dK3flfiIiIYOqUycyZM5uoqChSUlLYs2c3P/7QgX379sq9QJIkycF7dhYHyJ8/P9OmTWf27DlZbki+fPmS6dOncfnyZYoWK8b7iAhGjhjOzp07dXa2/J2KFi3G0qXL2LBxU5aOXr17AdCrdy+tMn3H0GHDstyTm10xMTFERn7QPA3Au7dvWbliBWPGjKZbt654e3sjSRJPnjyhS5efGDxoIJMnTZIbLC9fBspLNzo7O2dp6UalUsnJkyfkHPHSpUvj7Jz6fpIkiaCg1IZSlcqV9S5csmHDBsqWcaR/v5+5cvkyirTrVnohIW9Yumyp/B3arHlz+vTpoxVcKJVK4hMyfk8ZGBjQsmUrunVL7RgkbZWhS5cuqtVTcXV1Zdeu3axcuQpHR0d8fX0ZOXIERYsWoWnT7xk9ehTubq5UqujOmtWr5ZGS2rVr89tvRzl56jQNGjbUaoCWKFGC3r17U69e5r3LV69eZcjgQWrzOYYOG0aRIkXp2rWb3C7ZsGEDE8anbiKmYm5uTosWLTNsg3wLMTExrFq5ktq1a7Nt2zb5vIWFBXPmzKV9+w4ANGvWnMmTp6j14u/atZNKFd0ZOXIEjx490rnp5//3NldsTAwvX7ykTJmylE7rZPm7KBQK1q9fx927d0lKSmJA/35MnTpFbW7n1/TFgcKsWTPJZZxT71HYtpDebcnTT/pp0KAhbhqrTAAEvgyUN74pXLgIa9auo0yZMoSHh3P0t7++2CIjP1Cjeg06dEh9c8fGxrJlyxY+fPiAQqFgxfLlfN+ksTwsT9qQoueGjfJQZEpKCm/e6F7XPVeuXAwaPJg96dblVUXX48eNlT/4SUlJhIS84eFDH/z9/XWuuBL+7h0TJ06gXLmyrF61itWrVtGyRXO1x+bm5qa2Csa5s2dp2aIFBw7szzASzyoDAwO5xwTg/IXz8vDc58qVKxcDBw3C95Efnhs28sMPP8r3T9r/1KNHD3777SiLPBbrbCy/evWKSxf/uiA0atxYZ72voUCBAvIurSVKlMw0r/5L5M+fn6HDhlGmTJks914aGRl91Y2TJEkiRdL+Qv+aVHMU+vbtm+HRq1cvnavNfG1v3rzh0aNHFCxQkLxfsYflc0RERDB//jwuXLhAyZKlsLCwwNDQkEaNGuHi6sq8uXPxWLSI6Ohowt+94/KlS7i7u8sTgbPKpkCBTCctkvZddfz4Mfr374eXlxedO//Erl275Txtj0UL6d2rF9evX/8q3zn/Jt27ddUaBatdq2a2l4ANCwvj9etX8gpMKgqFgnnz5sq9nSdPnODx49R02bdv3+L7MLWH89ix35k7dw4fPnxQG313dCxDIY3lW3Xx8/Pj8KFD8u9VqlTF1NSU3bt30ahhAxwdSrNk8WK1hquFhYXWIgqRkZFs376dxo0bYZ03jzxSfPLECRQKBYULF2HTpk1069adQra2jBwxkoKFCnHl8mX27dvLlcuXuXL5Mlu2bGHf3r8mOue3sdGZmmRpaUnfn3/Gzq44nTp15sLFSzrz+1Vy5sxJq9atmDBxotpjv3jhAmvXrOHp06dq9QcMGMCs2XOoVKkSCQkJOkfP8uTJw7jx4zNMGUtJSeHUyZP06d1b7W8MGDBAHk1RzbtQ2bx5Mx3at+P27dukpKToTTXJiI+PDxWcy2u1tzJrc6WkpPDy5Uvmz5tHpYoVGTdurNrKQNbW1ixfsYJ+/fvLQV6OHDkYPmIEc+bMVQsWYmNjWb9uHRXd3XB1qcC0aVM5d/YsCoXiP9HmCk9LkXZ1c83SZ/FrefnyJRPGj2P/vn30HzCQI0d+Y8rUqVy+dIkff/iBHTt2fPUOnuy9O7+iiIgIThw/Lv+umjxiaGio1gsxc+YMypUtS7NmTWnRojktWjSnWtUqFC1SmB07dqjdvpCtLe3ataeQrS3dunVn3vz55MmTh1evXnH48CG1HuNx48ezecsWfHweYJLLmFzGOTE1yUW3rvonchsYGNDk++85eOgwjRo3ls8HPH9OZGQkfn5+VKlciZIlStChfXv2798n/01ra2sGDhqktULCIo9FjEv3pietcbx7z17WrfdUe+OqPgAZReLZ4ezsTPsOqVurh4WGcvDgr3pzD3/6qYs8BK5qSOiTL18+evfuze49e3gWECDf7tbtO2z6ZTPNmjfX2bsrSRLHjx2Tg8c2bdpmqTfnc+XPn5/lK1Zy9tw5Ro0eneU88Ox48sSfli2aazU6snu0bNE8yxN8JUlCoVCo9fIkJSXh5XWNZ0+fktvM7Ku9h1Q5mqqdhVVr/0dFRWV4xERHk5ycjFKZQkxMav3s5olHR0dz9+5dvL29iYiIULv/yMhIrly+zPRp03jx/DmVKlXC+isGXdkVGRnJ0qVLOPPHH4wYOYru3bvLr4GtbWFmz57DDz/+yOUrlwkICODM2TPcvn2LGjVr6RxCViqVPPF/kuGOv/pIkoSfnx+jR41k4oQJfFQomDJ1KuMnTCB//vy0bt2GjZt+wd29Ir6+D+nf72f69O7NiRPH5U2xrly+LK9Tv2f3bkLDwuRJ2qrzPg/uExn5nsOHDsnnVL13p06ezPT2upY2/Lu4urpppShVrVpNZwAWHR2Nt7c3b8PC1N6DDx8+ZOuWzSgUCooULiJ3RCgUChYtWqjWyzpw4EDatGmLgYEBderUYc7cvyZrbtiwgTatW7Fr518bMFWvXj3DBixp86I2b/5FrQNo7949lHcqR5/evXVOoFY1yh/4PGTf/v1a1ysV1Ujxixcv5PkORYsWY9369Rw48Cu10yY9m1tYMGHCBBo3bkTjxo0YOmSw2utaqmRJvWvVV61alTNnz7Jt+3ZcXFwwMDAgJSWFhw8fcvTobyxauJDu3bpRrWoVLMzNKFmiBH379NFasUeXDRs20LDBdxQrVpQCNvnlNkDdOrXZunWr3IDPKOUvMjKSadOm0r17N7X/aeDAgQwaPFitoT10yFC1QOf69ev8+OMP3Ey34/O39uHDB4YMHkTZMo7MmjVT6/NVuXJlDh/5jW7dumuNBOXIkYOBgwapNdrTe/r0KevXrSPifQS5c+f+T7S5AgKeER4ejrOz8zftZFQJDw9n1cqVdOvaBW9vb+bNn0+vXr0wNTXlp5+6sHnLVtzd3Tl96hSh6VaZktIWuPgiiUnJkr5jxoyZEiAB0rbt26XEpGQpKjpG6tevn3w+u8fFS5fl+w+PeC+tXLlKatS4sfTk6TMpMSlZSkhMkpYuXaZ1u4yONm3aSq/fhEiJSclSTGyc9PzFCykhMUntfzl77rxkZ1dcsrMrLm3fsUNSfIyXEpOSpRs3b0mFbG217hOQGjRsKAUFBWs9L4lJyVJo2Fupb9++UtWqVaUHPg+lxKRk6WN8gjR5yhS1+7C2tpbGjhsnBTx/Lj9/W7dtk5ycnKRjx45L23fskCwsLOT6HTr8IL0MDJT/zuUrVyUXFxcJkEaOGiXFxMZpPZYvOe7e+1MqW7asBEh2dsWl6zduatX5u45Hfo+lqlWrSoBkYWEhnThxUqvOv+WIjomVpkydKrm5uUmdO/8k9erV64uOzp1/ktzc3KQpU6dK0TGxWn8v/RETGydNmzZdcnBw0Hls3PSL1ucjq4fq/+rVq5f09l24tHLVaq37/9zj8JEjWn8vo+NZQIDUpk1brfvRPDp0+EF67P9E6/ZZPQ4fOSI5ODhk6bnXdbx69VoaMnSo5ODgIK1YsVLvfURFx0je9x9I17yuS3Xr1ZM6duyk9l2wc9cuqW69elKPHj2k1q3bSA4ODlKPHj3k776MDtXrdPTo79KMGTMlNzc3ycHBQerVq5fkff+BzvdDVHSMtOmXzVLlypXl57JXr17Sm5DQr/q66ztu3rqt9ZgyO1SvVXbfS6pD9X/p+ttv34XLn8e378Ll85m9DzXff7du35EqV64sf+e3atVaevXqtdrfUnyMl+bNm69Wx9HRUQKksmXLSt73H8h1L166LNdr3KSJFBIaJt/HL5s3S9bW1vL1bPuOHTqvd23atJUuXLwkxSckqj2OqOgYac/evVLt2rW1btOyZSvp9es3avU1j8CgIKluvXpatyXtenP23Hmt22R2pL9m6Tvq1q0rzZ+/QLpx85YUGvZWOnv2nDRk6FD5OdR3NGveXAoOfqX1N9M/x/369ZOiomOkyA9R0tBhw9RuP2DAACnifaTW7ROTkqUHPg/l6xsgzZs3X26HqI6Hvo/k672Li4v00PeRzseQnUPVdktM+y5q1aq1Wrm1tbU0YeJEKTTsrdZj1nW8fhMiTZg4UX5fqY4JEyeq/T//n9tccYqP0pw5c6XvmzaVHvk91ir/Gofq+2bK1KlSeMR7ad68+ZKDg4PUr1+/DL+zfR/5SecvXJTWrfeU1q33lObOnSdVrlxZmjZtus7/JStHxrOTsiD9kmK6vH//np49e+gcCrO0tGTgoEH0HzBATscwMDCgX//+mFtYsHvXTq5cuaJ5M5mbmxs//PAjvXr3xsbGBtKGq3Tl5tapU4fNmzdT3N5ebYa7rW0hHB0dtdb5dXR0ZODAgVq7c6pYW1uzdNlyEhIS5KFTIyMjmjdvwd49e6hYsRJt27WladNmaj0/pqamdOnSlQ4dfiBnzpykpKTw+tVrFi5cwOjRYxgxUn0zm+rVq7Nr9x4WLVxI374/f/VcWmdnZ4aPGMngQQPlSWOa61b/HRITE9m0aaM8mtD355+pU7euZrV/naJFizFr9uxsp49oUu2qnBW5cuUif9rnIT0zMzM6d/6Jtm1Tey6/Bqdy5Rg1eozm6c+i63ObEWvrfLi6upI3r3aPO2mbJ9WoUYMGDRrq7JX/u0S8f09YaBgjRo6iZ8+eekeuTE1NKVOmDAcP/kpSYiKdf+qMrW1hubxo0WKEhoQQGhICQKVKlRk6bLj83ZcVFpaWpKSkYGllxZChw/jxxx/1pvaZmprSo0cPWrZsyYEDBzh+/Bg/9+tP/vz56dGjB507d9a8yVela9Txf8nQ0FDONU8/ipMnT17KOZUjb948REZ+kFOIypVzomrVqnTt1lVtBSk3Nzd+O/o7c+fM5s8//2TuvHlaCxvkyJGDHj16cP/+fdq1b0e7du159uwZo0ePolKlSjp7dTXlyJGDbt26U9yuOCNGDGfw4ME0afI93t7erFi+HGtra7p07Uq/fv31pkSamprSocMPtGvXnqCgIA4fOsRvvx3h8ePH9OrdS20/Hl3y5rXGqVw5rly+LJ9zdHTEzc2dfv37Z7rcqi6auzg7OjpSvXp1ataqTcWKFXF0dNR6T9etV4+69eohSRJRUVE8ffoUb29v7t29g4+PD/fv38fCwoKhQ4bqveZrMjMzY/bsOXxKTmb37t2MGTOWkaNGaf1tlbJly7Jh4yaGDB6EjU0BevbqpdVzn1XOzs5s2LhJK0WMtOV3hwwZzMULFzSLKFCwIHPnzePt2zAeP35Mt+7dGTVqdKYbqaVnY2PD7NlzGDZ0GAcPHuSXXzZRokRJhg4Zqvb//H9uc8XHxxMUFEj58uWxTftO+JaMjY3p2bMnDRs1wsXFRecIB2n/q4ODA88DAli+7K9N7ZydK9CufXud/0tWGCQmJUuaJ1X8/f3liVT2JeyxsyuOUqlU2+hEc5MSTYmJidy/f5/EtLQCp/LltZaE/F9SPb7k5GRKlLDHxCT1Q25hYaH3gp4R1RCPvhdSl6ioKMLDwyldurTOL2vScvkMDAz0ln8JhULB5EkT5aHwBQsWMmLkyGz9D19CkiT2798nb/zTqlVrrR1C/22USiXPnj3j48ePlClT5osbPQqFgidPnpA7d24cHBwyfW0+fvyotjyaoaEhZl8h5Uj1fyUmJlKuXLnP+oz82yQkJJCQkICRkRHm5uaf9Rl8//49efLkydLzr1QqefjwIWXLlv1qQ9ovXrzg/fv3lC5dGmNjY5RKZbY7A5KSksiRI0e2U53+TqGhIbx+/YaiRYuoBVn/RJ8+feJDZGSGjW2lUqn2nkm/Ko1KUlKSfN7Q0BArKyut1yj83TvyWluTI0cOgoODeB7wXN7o8XMoFApy5cr12Q3dLxUbG8vbt28pVKiQ3tSl7EhJSSE2NlaeN6QpICCA344cAaCYXTHatWsvf/eFh4cTGBhIpUqVdN5W09uwMBISE3U2zmPTViBUfvqEUY4cuLi4yK91REQEfo8eAWiVpafZ5lK13dILCgoit6lphu+9rEpJSSEhISHLa/b/f2hzRUREcOrUSRwcUoPUbyEpKYnHjx+TK1euLF3z00tOTpYXHfga1/4MAwXhvyM6OpqHDx+SolSSI2dOXF1dv7hxm1UKhYIHDx7wKTkZ0npe/s1BgiAIgiAIwv8HIlAQBEEQBEEQBEFL5uNkgiAIgiAIgiD854hAQRAEQRAEQRAELSJQEARBEARBEARBiwgUBEEQBEEQBEHQIgIFQRAEQRAEQRC0iEBBEARBEARBEAQtIlAQBEEQBEEQBEGLCBQEQRAEQRAEQdAiAgVBEARBEARBELSIQEEQBEEQBEEQBC0iUBAEQRAEQRAEQYsIFARBEARBEARB0CICBUEQBEEQBEEQtIhAQRAEQRAEQRAELSJQEARBEARBEARBiwgUBEEQBEEQBEHQIgIFQRAEQRAEQRC0iEBBEARBEARBEAQtRtOmTZ+peVL47woNDcHf35/cuXNjamqqWSxLTk7mj9OnuXnrJkWKFCF37txyWUJCAhfOnwcDA6ysrDA0/Lx4VJIkHj9+THz8R6ys8mgW6/Xs2TMSExOwsLDULNLL19eXt2/fYm1tjZGRkWaxLCAggMePH2NpaUmuXLkwMDDQrJIhPz8/PD3XY2VlRYECBXTe/uPHjxw+fIhHj3wpWbIkOXPm1KzyWSIiIjh06CD+/o+/6v0KgiAIgvD/k0FiUrKkeTK9iIgITp06SVJSsmZRltkWKkTjJk3+5w0TSZKIi4tDqVRqFn0WQ0NDzM3N5YZwSkoKcXFxpKSkaFZVY2JiwocPkbx+/UazKFMWFhY4ODhgZGREaGgIe/fspVu3bhQoWFCz6mc5ceI4E8aPZ+eu3bi7u2sWyxISEvDwWMSD+w9YumwZ9vb2ctnTp08ZOXIEdsWKsWDhIvLmzat226xS3U9ycjLjxo6jUePGmQYdL168YOqUKQQFBTJ37jy+a9BAs4qWpKQkli1dyq5dO1mxYiWNGjfWrAKAUqlk/bp1eHquZ/qMGXTs2EmzSobi4uKYP38e58+dY/qMGTRv3kJnoBAVFcWE8eMAWOSxmDx51IMkSZIIDg4mb968WFpmPRgKDAxkzOjR5M+fT+f9CoIgCIIgpJdpoKBqXCQmJVKkcGHN4gylpKQQGBREnTp1GD9+AiYmJppV8Pb2pnu3rpqnv5iuhq6qcXtg/36185+rVq1aag0uVQPPy8tLs6qaRR4eAEwYP16zKFMdO3Vi/PgJGBsbs3PnThZ7LKJWrVpMmToVO7vi8uv15Im/5k3VqJ6f0NAQXr9+Q+nSpcmbN+9XCRQOHz7E9GnTGDd+Aj169NDZGM4KSZLw8vJi4cIFhL97R+8+fenVq5fO9xFpQe3sWTO5cOECQ4YMpXefPnrrpqd6zqyt8zJ/wUJsbGw0qwAQHh7O5EkTefvuHcuWLad06dKaVfSSJIlDhw4yc8YMOnf+iTFjx2JqakpSUhLJycmYmZnJdTMKFEJC3rBt6zaOHv2NYcOH07Vrtyw/vyJQEARBEAQhO7IcKDRu0oSBAwdqFmdI1ZgEMg0U7EuUyHYgosubkBACX77U2dBNTExk08aNPHzoo3Y+O1T3D1CvXj0WLFwk9+p+/PiRY8d+Jy5OoXEriP/4kZOnTvI+IoLFi5fg4Oigc0Th99+PcuTwYaZNn07JkqU0i9VGFJRKJdu2bWP5sqW4uLgyddo0cufOnWFgFxn5gceP/eTnRzMw0PxdH32BQnx8PPPmzcXr2jXWrluPk5OT5k2zzc/PjwXz5+Pt/SfTpk+nU6fOmlWIj49n6ZIl7Nu3V60hnhVZDWxu3rzJiOHDaNykCVOmTM3y/QM8evSIkSNHUK5sWabPmEn+/PmJiYnBw2MRMdHR8jl0BApWVla8efOaHdt3cPTobygUChwcHenTpw/ff98UY2Njjb+m24MHD+jf72fc3NxEoCAIgiAIQqayHChk1kOdEVUveEaBwtBhwzMMRBISEkhISMDMzCzDFCZPT0/WrF6VaUM3u1JSUjh/7hwrV60k8OVLGjZqxLhx4yhatJhmVS3pG/SjRo+hV69eOvPg4+PjWbhwAY/9HrNk6RLs7IprVtGS/r6rVKlKn759WbF8ud7ATjMQyOx3dDRc8+TJozdQePjwIcOHDaVW7drZbkxnJDg4iHv37tGiRUuthnF8fDwrV6xg166ddOrcmdGjx6j10OuiGklJSEhg184d+Pv7M2LkSIoVs5PrGBkZUaZMGczMzNTSk/r3H0CNmjXV7i+9fPnyUbJkSfl31UjHY39/5s9fQJUqVSBtlGH37l0sXLCA/v0HMGToUIyMjOTnW6lMoVu3bpw8dZKTJ04A4OxcgT59+lC3Xj2dn6eMqD5rGX0eBUEQBEEQVLIcKNSrV48ePXtqFmcoKTGR1WtWkzNnTr0Nk6wGCroasLp8i0BBoVCw+Zdf2L17F0CmKTBJSUmcOnUSV1c3ihcvzsmTJ5g9axatWrXOsKc7/N07xo8fT568eZg9ew4WFhaaVXRKSEhgz549uLi4kD9/frURoOTkZBQKBcbGxuTOnVvreczsd7IRKKTP4W/arBnlymVtNKFy5cq4urpy8cIF9u3bq1mcqbg4BQ8e3AfA1dUNc3PdQULdevXo2rUbpHs/ZaRMmbLy/xYQEMDo0aN48fy5ZjUt6d/LERERzJ8/D69r13TOS0g/b2HmzFk0a95cZwpb/fr16fxTF6pWrYqxsTGxsbEYGBhgbm4u18mMCBQEQRAEQciOjGeGphP5IZJnz55l7wgIICY6WvOu/lX8/f0ZPWokGzduoGjRYqxctZoBAwZk2MgKCAhgx/YdTJ40iSNHDrNhwwaqVavGwEGD9AYJAB+ionj77i32xe3VVhHKjImJCX369KFy5cqaRfj6+lK7Vk127NihWfTVhYWFcv36dQBOnzrF8mVLs3S8fv0KgI/xH/Hy8sr2oQoSAB48uK9VrjpiY+PkeiotW7Vi1OgxasfQYcNxd68o11HNlXjx/Dm9e/dh67btOo/Bg4cAULiwLQDv3r5l0sQJnPnjD2rXqUMOoxxs2bKFzZs3M3fOHAb078eokSO4c+cOCoWCnTt3EhwcJP9dKysrunXrzm9Hf2fV6jXUrl1bHk0JCAigYYPv2L59u1z/xInjOJd30nuo5gId2L+fypUqapXrO06cOC7/DUEQBEEQ/juyHCgc/PVXevfqma1jQP9+nD9/XvOu/hWSkpI4cuQwffv0xsvLi3bt27Nh40aqV6+uN4ddxcnJiUmTJxMTG8P0adMwNzNn5KjRcg66iqenp1qDrH27tgQHBbFp00ZcXSpoNdg8PT3l2yqVSt6/f692f/9LkiRx8eJFfHwe0K59ey5cuMg1r+tax8xZswCYOWuWfK5hw0YAtGjREt9HfnoPn4e+PPR9pHU+q4euEas6derQt29ftaNXr144ODrIdUJDQzh39iwuLq50/qkzVapU0XkUt09NFVOlleXJm5dSpVInPP9x+jRjxoyWg6N9+/bi5eVFVFQ0JUuUwNXVDR+fB+zauYvEhAQAnJ2dGThoEKVLl9Za7Skk5A0KhYK8ecU8A0EQBEEQvo1MAwVzc3PatmvLunXrtRpemR3e9x/g4bGYypUq68zJ/6eKjIzEY9Eipk2dCsCUqVOZNm26VkM/I5UrV2bGjJnY6phQrKlLl65avdrpjz59+qqtxKNUKjl69De6d+/GmT/+yHQ51r9DaGgIf5z+A9LSaUxz5yZPnjxah2pExdTUVD6X0eiMSkjIG6ZPn8bJkyeQJO1suVMnTzJq1Ej+/PPPr/58XLhwAW/vP/m+aVMKFy6iWSzTXHbX2NiY75s2ZZGHB1u3befgocNc87rO9Rs38Xnoi+8jP349eJANGzexctUq6tWrR2hoCO8jI9XuRxeFInXCfP78f70vGjZspBWYpT/WrVsPkGEgpzouXLhIu/bt5fsWBEEQBOG/RytQiImJYcaM6Qzo348B/fsxZfIkrl29yu7du+RzWT2GDhnM0aO/cfTobwwdMlg+v2b1ahITEzX/NAkJCcyePUurJ925vJOcT969W1etMufyTsyePYuEtJ7YL3XgwAH27duLu3tFNm76hc6df9KaQKuLUqkkJiaGqKgooqKicHBwoHfv3lhb5yUlJUU+HxMTo9aobNa8udyb3bVrVzp06EDXrl3lc+07dMDaOp9c39DQkGLF7DA0NGTatKns3buHpKQkufx/QdWYBoj6EEVCfLxmFQDev09tBBcsWEizSKeoqCi2bNnCjz/8wG9HjnDu3DmtkZT4+HiePn3KdS8venTvxqCBA7h586ZWw/1zBDx7xqFDh3B3r0jjxo0yHE0KCQnVPIW7uzstWrSkSpUqlC1bljx58mBpaak1QpA/f34mTJyIx+IlFCtWjNxmZjx9+pQnT56o1SMtpena1avY2NiorVxkYmKiFZilP2LjYgGwMLcgr7W1Vnn6w9LKSl40IG9ea/lvCIIgCILw36EVKOTIkQMnJyeqVqv+zY6SJUtqNZQADAwMsM5rTa1atbQO+xIlIG2yqmZZrVq1sM5rnWEj7nN0/qkz5cuXz/L9vnr1it69elG7Vk35mD9vHpcuXaJtm9byud69evHqVWpevqbz589Ru1ZNzp8/p1kkMzAwoEqVKsydO4+iRYuxYP58PNevJ15P4/xbe/niBUcOH8HdvSINGzXi7bu3fIiK0qxGcnIyYaGh2NjYZDoHIyEhgePHj9GtW1eWLV1CXmtrFnl4sGiRh9bIjqmpKcNHjODQ4cO0btMGLy8vfu7bh8GDBnL79u0vGmEo7eDA2rVrGTlqFFZWefD19dU5oqFPYmIia1av1gqidR3PA55jamqKubk5lSpVIjw8nL59emsFxQ0afMeFCxdwr1iRokWLav7JTKUPArIio3k1giAIgiD8/6XVWs+dOzedOnWWe7N79OhBhw4dvuj48ccf6d27t3yfzVu00NlQyZUrF0OHDWPDxk1aR8uWrbArXpwZM2dqlW3YuImhw4aRK1cuzbuEtEanqjc/K0dS2mhHfHy8Vpm+4+PHj3KalmbKkLt7RYYOG86o0WOoW7eu5sP7bG5ubsyZOxcXF1diYmI0i/820TGpE9bbtG1D0++bEhwUpHN1oISEBELDQrG3L4GNnjSupKQkzp45Q6+ePZk4YQLh797Rt+/P7NixU+fSqCoGBgYULVqMefPmc+DXg9SvXx8vLy/69O7F8GFDvyglqXDhIpQqVYo5c2YzatRI7t69q1lFL0mSiPwQyf3790lI0B5FI21vCy8vLz7Gf4S0/6Vjx04sX76Chg0bagXFDRs2ZMbMmcyaNTtbOzO/evUaAGvrz9spWxAEQRCE/xatQEGTatWcLznGjR3zRQ1ZhUJBUFAg1nmtsbDI+nKQKqpe+qweGzduAGDmjBlaZfqOHTt2kD9/frp376GVMuTg6ECvXr3o3LkzVnnyYGOTHysrK82H+VmcnJxYsnQJI0aOzLDnV7USz7fg5ubOgoULadCgIaVKl8aueHF8fHxITk5WqxcREUFgYCB2xe0w17H06/Xr1+nRvTujRo3k5csXtGvfniO//cao0aOxts5a+ouBgQFOTk6sWr2GTb9sxtm5ApcuXaJH924cOXJYszpBgUHcuXNH7bh37x7vIyLU6uXJk4dWrVoTEx3N8mXLePHihVp5ekaG2vNxihYtxqzZs7UC3A0bN9Grdy+1uikpKSQkJFCtenWWr1ipVX/lqtX8+GPHLC+fS9rIRkR4OAAFbApoFguCIAiCIGjJNFBQ2blrt9ZkZd9Hfizy8KBMmbIcP3FSq8z3kR9Dhw3XvKtsCw0N5dGjR9y/783ChQsJDQ3RrJKh3Ka5tXplMzpUaU7lyjlplek7shLAhIeH8/TJU8qVc8pWT3BmChcukmmj8VtPJnd0dMTa2hpbW1vKlCnD/fv3effurVodP79HPHv6lFKlSusMaooWLYKhoSHNW7Tgl81bGDNmLLlzm2mN3mTliImJoVy5cqxbv545c+fStFkz6tWrr/knWbdubZZX66pevTr9BwzEx+cBK1euIFLPpOOChbI2/0KfmJgYxo0dk2GAnZSUREjImyynQamCbRsbGwoULKhZrEWpVP7PUtkEQRAEQfhnyHKgoFAotBpjUVFRxMfHkyKlEBcXp1UWlS6N53MplUpOnjjBi+fPadioEXfv3GHokKHcv//X2vmZ+a5BA61e2YyOli1bAdCrdy+tMn2HaiOvjAS+fMmTJ/64urpm2nDX1Sutz9eYtPu1WFhY4O5eER+fB9y6dUs+Hx8fz40bN7CxsdG53wNAsWJ2rFu/noULF/Hp0yetUZvPOW7cuE67du11zm0gi/soqBgZGfHjjz/S5PvvOX/uHEeOHMnyc//69StmTP9rkYD0x7at2zSr65WUlMSVy5fp0b07Y8eM5dWrYM0qOoWFhREQEJBh2ld6ycnJRL5/T5kyZcmbV6QqCYIgCMJ/UZYDhYED+ms1wmrXqsnMGTN49vQpnTt11CqrnS6N53PdvHmT3bt30eT775kzZy4LF3kQExvDuHFj/zFLg2aVUqmkcZMmamv0a1Ite5nVXmmlUsmmTZvYvXsXsbGpq9qk9zYsDACz3Lp3K/4ckiTx4sULAl8GahYBULNmTUqWKsXFCxfkFYoCAgLwunaNWrVrUyJtxEaTgYEBefLkUZvonr4hP3jwEEqWKqU250M176NkqVIMHjxEPtelS+rmYir6ArOs7KOQnqWlJX37/oxt4cJs3ODJlcuXNavolDt3blxdXbUm9letVp1SpUtpVteSkJDAlcuX6ffzzwwePAhf34fYFLAhKUk9vUsXSZK4c+cO4eHhlCtXjjyi4S8IgiAIQhZkOVD4u1OPJEni1q1bzJw5A0srK376qQuWlpbUqVOHxYuXYGlh+Y9ZGjSrGjZqxPLlKyhSRPdKNUqlktCQUOyKF8fMLGsN+48fP/LkiT+7d+8mNFR7ec5Xr19jZmZG3izm+GfmzZs3LJg/n969enL79l8jBumVKFGCJo2bcPHiRS5evEB8fDxHjhzm48ePNGzQUGfakT7pG/JdunbFtlAhec6H6ryLqxu2hQrRJd2Sss2aN9e8q6/GycmJnj17YlOgADmNjZEkiYSEBK1Uq/SsrfPRvkMHraCkb9++1KlTR7O6LDIykj17dvPTT50ZPHgQ9+7dpWGjRuzYuYvly1dQunTqhm4ZCX/3jsuXLgFQsWJFnQsJCIIgCIIgaMpyoPD06ROtSZ937twhKDCI+IR4Hj3y1Sq7c+cOYWHajdfMJCUl8dtvRxg9aiQx0dGMHDlSLV1FtdpPqVKlWTB/PuvWrpV74v/NYmJiePzYD7tixdQ2WMuIaoJwmTJlsLVVn7CsUCh48eI5Dg6OFCiQtfvTJSUlhZSUFLy8vOjU8Uf27NmNk1N5nJ0raFaFtN771m1a4+LiyoYNG1iyZDEnjh+nVu3aVNKTdvRvYmBgQIcOP7B37z5q166d5eVzs8vLy4vWrVoyf9483r19S7du3fn92HFWrFhJxYoVdS4xrEmpVHL8xAlu375FjRo1cHVz06yiU3z8RxSKjxgZGWFo+G3+P0EQBEEQ/tkyb2mkmTN7ttakz969erJu3VqCg4KYMH68VlnvXj05+OuvmnellyRJPHnyhKlTp8i7Ik+fMYNmzZprNcacnJyYv2AB7u4V+eWXTcydO0fv5NJ/Cz8/P7y9vSlatFiWdisGCAoM5NnTp5QpUxZzc3Ps7e05dPgwAwcOlCeBm5iYyLn0LVq0xPeRH+7u7pp3pdetmzfx8fEBwL5ECRZ5eLBy1SqcyjtpVpUVK2ZH125diYmOZv++fVhaWdG9e4+vOon7f8nU1FTnBHIHR0fypNsETeVz5yhUqlSZRR4e/HHmLBMnTaJkyZIYGBjw+vUrvL29M50j8eeff7J37x7MzMxo375DlgPQxMQk4uPjyZs3D5aWulfoSkhIwNc3tYMgLDQ0yxOrBUEQBEH4d8g0UMiXz5pRo8dw8tQprbSirKQerVu3ngYNG+pd/z49Hx8fhg4dwskTJ+RdkZs3b6G359Te3p45c+fi7l6RkiVLYW6e+cpD/yRNmjRh67bt2NvbExERwf59e1EoFOzbt5eJEyfw+nXqpmw2NjZMmTqVJk2aqN1ekiT8/PwAcHFxUQum0k8Cv3nzBiOGj8Db21urMVexYkX5MehTpmxZSpUqTefOP2W6n4GKgYEBjo5lKFq0GACFbQv/vwkSdJEkCaVSiaGBoVZQy2fOUahVqxYrV62iRYuWWu/t8PAIunfryqZNm9TOp3f37l1mzZpJaEgIrVq1pv5332lW0UuSJFIk/fN/goODGDF8GJ07daR3r5506NCe06dOab2/BEEQBEH499LdAgeuXL7M5s2bOXs2dYfgs2fPsXnzZq3j6tWrREa+5/ChQ1plmzdv5llAAHFxCvbu3cvmzZt58OCB5p+Subi4MGH8BKZNn87GTZuytCuyvb09a9eto3v37pk2Xv9pSpYsSZUqVTAxMcFz/XouXLhA167d6Nv3Z27euEHv3r05ceI4JiYmVKxYkZIlS6rdPjY2lidPn1CmTFkKFy4sn5ckidOnT7F79y4aNGjA8uUrABg6ZDD79u1Vm9Nha1uYKlWqZLiyTcmSJfFY7MGYsWOztJ+BJEl4e3szccIEnjzxx654ce7du8uIEcM5ceL4v2ZOSXYkJiYSpmOOiMrnzlHQR7V0qa7N0yRJ4urVq0yaNJHAly9p0KABAwcNytbckNDQUJ49fYp1vnxacxqSk5M5+OtB7t+/z7DhI1izZi3Ozs7s3LmTkJA3anUFQRAEQfj30hso/C8YGBjQqHFjOnXqnK1GjaWlZZZTdTIjSRIpmaRzfE0RERHMnj2Lffv20qBBA/r178+IkSNZvHgJuXLlYsL48SyYP19nWtXr16/xefAAxzKOckqJJEncvn2bFStWpKb79OhJ4yZNWL5iOc7OzsybOxePRYuIjk7dTTmrihYtlqXXJD4+nm3btjFwQH9ev37F0GHD2bdvP0OHDSf83TsmjB/P6FEjefTo0T9ixaoJ48fjXN5J7ahcqSIH9u/XrJqhiIgIQsPCsLS0xCx3bs3iry4iInXzNEsL9VGa+Ph4NmzYwNgxowkNCaFBgwZMnTpN59Kw+kRERLBv7x4AChUspPXZUigUPHniT9NmzejRowf1v/uOFi1b4uPzgHfvUh+XIAiCIAj/fgaJSclflCtw4sRxtmzewtJlyzJMX9HH29ub7t3Ul7L8Gnbu2p1pHn5ycjJKpVKtIRQUFMT0adO4d+8ua9aszVa6hqaHDx8yfNhQvmvQgPHjJ6j9naSkJM6ePcP69esJfPmSVq1bM27ceLUe+9evX7F48WLOnzuHs3MFJk6ahKurqzzKcuDAfmbPmsX4CRPp0aMHSqWS06dPsWLFCmKio5k+YwbNm7eQ60dGRrJ4sQfHfv+dho0aMXHiRGxt/xqJUCqVrF2zho0bN2T6/CUkJODhsYgH9x+wdNky7OzsuHXrFitXrMDX9yH2JUowYvgIGjZqhKGhISkpKVy7ehWPxR4EvnwJQP369enU+SeqVKlCSkoKx479Tlxc6qT0t2Fh7Nmzm5atWuHg4AhAYkICp/84jZWlFbVq15Z7uu/dvcPrN29o+n1TcqU9x7pub25uRqtWrcmdOzcnThxnwvjxlCvnpNUrn5KSQmBQEJYWlmrv6/j4ePz9/SlQwAYzs79SgaKioli3bi0nT5ygbbt2TJkyVQ6qNJ8nzc9ISkoK27ZtY9nSJSzy8KBFi5bExsYyffo0fH19mT17DtWqVVNLv3v39i2Llyzm7p07rF23HicnJyRJ4vHjx6xcsRwvLy8AOnf+iWHDh+vcBTwyMpJZM2eQkJAAgKWVFQ4OjgQFBXL79m1CQ0KwLVwYD4/FWu8D1eOLjopm3vx5FChQkE2bNrF/31758QiCIAiC8O+nFSi8fv2K5cuXE6djTX5dIiM/EBwcRNmy5TAxyaVZrFOFCi7069+fXLlyyYGCfYkSFEmXPvO53oSEEPjyZaYNXYAHDx7Qv9/POldMcnFxZfGSxXqXMtUlJiaGpUuXEBYaKjc2Q0NC5IY8aQ3H27dusXnzZu7du4uZmRmDBg+hc+fOWj23pPXebtq4kV9+2YSVlRUTJ02iefMWJCQkMHfuHI79/jvbtu/A3t6elStXcOTwYWwLF2bC+Ak0bNRIK3VLoVCwauVKHj58yNx587h27RoeixZSrpwT8QnxBL58iZubO4uXLFYLIjSlbwAPHDiQs+fOcvLECQCat2jByJEjKVy4iObNiIyMZPu2bexLm48B0L5DBwYPHsKM6dPkRu63UKtWLRZ5LCZPnjxyoKBqnKenr3EfExPDpIkTuKxn7wTbwoWZP38BVapUkc/puq/g4CDGjhmLn98juZ6NjQ2rVq+hQoUKSJLE7t27WLhggVyuS+s2bZg8eQrm5uZcuniRKVMmEx0djZWVFUOHDaNDhx/0puPFx8ezcOECDh08qFkEgJWVFVOnTqNps2Za7yGAUydPMnPmDHLkyEG+/Pl58fy52uMRBEEQBOHfTytQiIiI4NSpk1nayOlz2RYqROMmTciZM6ccKAwdNpyBAwdqVs02T09P1qxelaVAITAwkDGjR/Pkib/aeWfnCowaPZqqVavqbCTpo6vx1eT775k8eYqc+hEREcHsWTO5cOEC9evXZ/CQoZQrVy7Dv6NUKjl+/BibNm1ixoyZVKlShYSEBP744zRnz5xhytSpvH79hsmTJ1GoYCEmTpqEk5OT3vtMSEggOiqKgoUKceniRYYOHSKXOTg6MmzoML5r0EDv7dFoAE+cNImdO7bz6vVr+v3cj0aNG+ttoKqEhLxh29ZtPHr0iDlz52Jvb09cXNw3TUcyNDTE3NwcQ0PDDAOFxMRENm3cyMvAl4waNUqekK06//ChD3FxCh48SN0d3L5ECSpVqkSXLl1xdHRUe950BQpxcXGsXLGC4OAgAExMTGjVqjXfNWggbwyXlJTE3bt3efz4sXxf6RUrWpQ6devKIxdKpZJt27bh/ec9hg4bTtmyZTVvokapVPLs2TPevX3L8xcv5Oc9Z86clCtXjjJlymQ4+VypVHLmjz/YuXMn4RHhtG7Vmh49e+ocvRAEQRAE4d9JK1D4u3348IGAgADy5cunNVn3c7x48YL3799TunTpDCfoktbYUSgUao1TY2Njcn9mjrkkScTFxclLVhoZGWFubq7V4A4JecP795GUL19e74pOmiRJ4v379+TLl09rdSMDAwMMDAx4+vQpdnZ2WZpL8KVUDc2PHz9SpkwZkpOTyZUrV7b/dmJiIsbGxlrPkZB96d93giAIgiAIX+p/HigIgiAIgiAIgvDPk7XubEEQBEEQBEEQ/lNEoCAIgiAIgiAIghYRKAiCIAiCIAiCoEUECoIgCIIgCIIgaBGBgiAIgiAIgiAIWkSgIAiCIAiCIAiCFhEoCIIgCIIgCIKgRQQKgiAIgiAIgiBoEYGCIAiCIAiCIAhaRKAgCIIgCIIgCIIWESgIgiAIgiAIgqBFBAqCIAiCIAiCIGgRgYIgCIIgCIIgCFpEoCAIgiAIgiAIghYRKAiCIAiCIAiCoEUECoIgCIIgCIIgaBGBgiAIgiAIgiAIWkSgIAiCIAiCIAiCFhEoCIIgCIIgCIKgRQQKgiAIgiAIgiBoEYGCIAiCIAiCIAhaRKAgCIIgCIIgCIIWESgIgiAIgiAIgqBFBAqCIAiCIAiCIGgRgYIgCMK/1P3797lx4wYpKSmaRbKEhAT27NnNixcvkCRJs/h/IjExkSNHDvP69Su9j+ngwV/Zv38fcXFxmkX/E15eXpw8cQKlUqlZ9FV8+PABz/XruX//foavpyAIwt9JBAqCIPxrXL9+ncjISM3TXywiIoJ1a9d+k/vOSEREBAsXLODFixeaRZmSJImbN2/S7+e+zJgxPcPHHhAQwE+dO7FhwwY+ffqkWfy3kySJhw8f0qF9e52PKTExEf/H/syZPZuBAwbw9OlTtfIvFR8fj6enJ7dv385SozwpKYmrV64wfvw4pk2bSvi7d5pVvljevHmpU7cu48aNxWPRIuLj4zWrCIIg/O0MEpOSdXfnCIIg/M0iIyNZsmQx39X/jsZNmmgW4+npyaFDB7EvXhxDw6/XzxEZ+YHHj/1o0KAB02fMJH/+/JpVZDExMaxds4bAwJeaRdn2JiSEwJcvs/R3NcXExDBt2lSiPkQxe84cihcvrlkF0kYUPDwW8So4mEUei7G2ttas8rdTPaa4uDimTp2GpaWlWnn4u3eMHz+exMREFi9ZTJEiRdXKv4aIiAhmz5qJuYUFQ4cOpXDhIppVZAEBAYwePYr4+HimTZ1G7Tp1vur7T0WpVLJ+3To8PdezZMlSmjZrpllFjSRJSJKk87EkJyezds0aLK2s6NatG8bGxppVBEEQMvW3BArJyck8f/6c588DCAt7i5lZblxcXHFwcCBnzpxyPaVSybWrV3F1cyNPnjxq9/Fvk5KSQnBwMI8e+fL+fSSOjo6ULl2afPnyYWBgAICfnx9GRkaUKVNG8+bCf9h/8fNCuoabq5s7vXr1wsjISLMKnp6enD1zhqXLlmFvb69ZLJMkCaVSSY4cOTSLdPL29qZ7t66s99xAnTp1NIu1xMTEkJiYiLW1tc7HmZmUlBROnTrJ/HnziI6OxsrKiu7de9Cnb98sN+gePnzI8GFD6dW7Dz169JC/VzSpGuVKpZKJEydhamqqWYWkpCSUSqXOsm9B9ZgAxo+fgImJiVq5n58fQwYPokOHHxg0ePBnPcdZ8ejRI0aOHEGuXLmYOXMWlStX1qyCJEns2LGDXbt2Mn/+AqpUqaJZ5avy9vZmypTJLF68hPLly2sWyxISEti6ZQvR0dGMGDlS52un+kyVK+dE7z59tJ5nQRCEzGgFCjExMSxduoSw0ND0p7WYW1gwatQoihYtplkkCw0NYd/efRw8+CvR0dGaxdiXKMGgQYNo3LgJxsbG3Llzh1UrVzJn7twMGwH/dC9fvmTpksVcunSJcuWcsLbOK/dYNmzUiJEjR2FhYcGM6dNo3qIFLVq01LwL4T/ov/p5IS0VZOmSJXxSfmLChIk6Gz1kI1BISEhg+bJl5Mufn3bt2mFjY6NZRY0qUNi5azfu7u6axV9VUlISu3btYoPnesqWLUffvn2pWq1athpxqsbroUMHWbZsOaVLl9asIsusUR4fH8/KFSt4F/6OyZOnZGtU43Nl9pgOHNjP+nXrWLV6DRUqVFAr+5okSWL37l0sXLAAd/eKLPJYpDWyEBLyhlkzZ9Ktew9q166tNyDTx9/fH0/P9cR//KhZpFNCQiJv372lWNGiOkcKVOLiFDx4cB+AIUOG6g0EXrx4wdQpU2jYqJHeAFwQBEEfrUDh48ePHDv2O3FxChRxcZw5e4bAl6lD7FZWVrRt2w7rfPkwNs5Js2bNdV5UkpKSOHToIGtWryY6OppKlSrTo0cPqlStKg8xK5VK7t+/z9Ytm8lvY0Pr1m1YsngxiYmJmTYC/snu37/PnNmzyZ07NxMnTcLJyUm+sISHh7Nr504uX7mMuZk59+97s8jDQwQK/3H/5c8L6RprBw4cYMmSpTg6OmpWkWUnUPDwWMSB/fsZOmw4ffr0ybCn/u8KFBQKBatWrsTrupda0Jdd4eHhTJ40kVKlSjN6zBhu3brF7l07dU4MTklJITAoCEBnylb6BmeT77//qsFCSkoK8fHx5M6dW62BnVGgoCpLSkpiypSpeoNGFUmSiIuLw8LCQrMoS968ec24seN4/jyAjZt+wdXVVS5TvTfz5MlDixYt1f4HSZJ4/PgxJUqUyPQxRkREkCNHDiwtLbWe//QuXrjAtm3bmDZ9eobBX3adOHGcFStW/C0jIoIg/P+i9Y2VO3duOnXqTN++fRk+YgQtW7aSy75v2pRhw4fTt29funfvofNiEh8fj+f69cybO5dPnz4xdNhwNmzcSMNGjdTyUI2MjKhUqRKLPBZjZGREj+7d8PF5oHZf/zaRkZFs3bqF5E/JTJs+nfLly6tdWGxsbBg+YgQ//PAD9+97q91W+G/6L39eVJ49e8aBAwdo0rgJpUqV0iz+IrVq1aJz586f1Rj/2t69fcu0aVP5GP+Rbdu206JFy89+XM+fP+fp06fU/+47jI2NqVWrFjNmzmT5ipVs2LhJ7Vi8ZCklS5SgTp06rF6zVqt89549+D7yw/eRH8uWLdf5vf65DA0N2blzJxMmjMfPzy9LE4ffv4/A/7E/9evVz7QBLkkSJ0+eoE/v3ty/nxrsZFehQrZUq1aNho0aab3/QkLe8CHyAw0bNtIKEs6fO8eIEcNZuWJFphOP8+fPT548eTIMEiIiIjh48Ffi4uLw8XmQ6X2GhoZkeQWmOnXqUqFCBXZs38b79+81iwVBEPTS/631GZRKJXv27GHjxg0A9B8wkH79+ukcDlUxMzNj0KDB1KtXT7PoX+fGjeucP3eOmjVq6u3tNDIyom3bdrRu00azSPiP+a9/XkgbTfn96FEAmjZr9v8qLSJ9Iy4gIICZM2fQrGkzZs2a/UWN8aSkJC5dvIibuztOTk6Q1iC3tS1M7ty5Nav/I3h7e/P61SvN0zo99nvM8+cB7Ny5kwH9+2V49OrZk9mzZvH4sR9zZs/WGSwkJSWxefNmrduqjsGDBnLt2jWePX3GmNGj1MpGjhjJzZs3GTliuNr5vn36MGPGdEJDQti1ayfbtm4lISFB80/LgoODWLd2LQEBATqDJaVSyZ7du/n06RPLVyynffsOmJqaolQqOXLkMMHBqSNCKpGRkXh4eLB//74sBQuWlpY0b9acixcvcvnyJc1iQRAEvb5qoHDl8mU2bvAE4Icff6RLly5ZuvDnz5+fH374ETMzM82if43k5GQe+T4CIE/evBn2FJqbm9OksfaKLsJ/y3/586ISHBzMlatXqFy5MkWLfv2VbfRJTk4mOTlZ8/RXdeaPP9ixYwdXrlzhwP79zJ4zl8ZNmmTYq5wVwcHBXL9xnWrVqmml23z8+BE/Pz+djcf8+fKTK1cutXN+fn5s2bIl097rL1WyRAmqVquW6f+elJTE3bt3cXNzY+asWVqjH6pj4KDBeHl50eGHDty6fQffR34cOnwYNzc3zbvE2NiYrl27Mnv2HFauWq11Xxs2bmL7jh3s279f6/yvBw+ye88erfNbtm7F6/oNeSRm0ODBGQb4dnbFqVK1KoMGDWTUqJFqDX9Jkjh9+hTBr4KZM2cudnZ/rV7l7+/PunXrmDhhoryEbmrwcISzZ85w+dIlfH195foZcXV1pUqVqpw6eZLw8HDNYkEQBJ0y/tYGChe21TylU3h4OHv27EahUGBmZkbTps0yHTZOz83d/ZvmBn9rSqWShMTUHqXEhASdF+r0ypQtg5vbv/f/Fb7Mf/3zQloDycvLixfPn1OpUqUMG1pfk0KhYOHCBSxcuACFQqFZ/NWkSCl4LFrIwV8P0Ldv3y8aRVBJ/5zNnzePDZ6eansQJCUlsXLFcjp36iT3fo8eNQpfX19OnjrJwAH95fP9fu7LiBHDWbZ0CUuXLPnmwUJWhISE8OpVMC1btSIsLEyzWBYS8gZAa+KxPiYmJhQsVEjneyw0NIRxY8ewccMGrVGBV6+C2bp1K76+vpl+p2emcuXKjBw5kps3brBx40bi4+ORJIlr167x4P4Dpk2bToGCBeX6ERERbPBcD0CvXr2wt7eXg4pDhw6yyMODdes91eZUZMQ6Xz7c3Ny4ceMGz5490ywWBEHQKdNAISs9nAAP0nYIBaheo4Y8JJ5VefLkwc29oubpf6Vbt24RFpbJqlHmFtgUyHglFuH/L/F5gbi4OO7f98aueHEcHPRPYNYnICCAsWPHaKWSDOjfj2FDh3D16lV8fX0ZPUo9naRXz57s37eP/fv2sWzZ0m8aLJA2ofd9ZKTOicbZFRLyhj9OnwagRo0adOzUSecSsA0bNdLq/T5+/IRar/imXzbTocMPVK9eg4GDBmUrUP1W/vzzHm7uFXFyKi8HA7q8evUaB0dH8uXLp1mULcHBQcycMYPLly9z5uwZrl65olZerJgdnTt35s8//6RNm9asXrVKb/pQZgwMDGjcuAk//tgRY2NjlEolnuvXs3ixB5aWlhw8eJDNmzfj6enJ2LFjGD5sGBER71m5chVNvv8eQ0ND7t69y7lz51i7dh0tWrTM8vWZtGu5Kqi4c/v2Fwc+giD8N2QaKGRFfHw8l9LlPZYsUTLbaREGBgbY69kw6N8gV65cFCiQ2hvk4/OATZs2ZbhTau7cuRkwYCDVqlXXLJKpVgxJT5IkFApFti9UycnJvHnzGm9vbyIiIrJ0kUhOTiYiIgJvb298fX2JiorK1t9VKpUkJibKvycmJmb6d3WlhCQkJBAbG6u3oSVJErGxsVq9gRlJSUkhJiYGf39/7t27x9uwMK2/mxFJkuQeQRXVfWZ2P3/35+Xjx4/4+/vj6+tLTEyM3udR0+e8fvHx8fJ7RNf7N73Q0FCePHlCCXt7ChUqpFmcqdKlSzN2zFgWLFzEes8Nao3g1WvWUqdOHZydnVm2fLlWOokqZWTatOnZfu6zq1nz5mqrn+kTHByUYRqJJElcvHiRQraF6Nz5JwwNDTNN5ckKIyNDncHG3y0mJgZvb28aN25Mvnz5eBv2Vuf7Jz4+ntDQEArb2n52oCBJEt7e3owaOYo3ISEsXLSIvXv36dzkz9TUlB49euDp6UnA8wDatmlNhw7t2b9/n87HlxFjY2M6dupI+/YdMDc3lzdukyQJFxcX2rRpQ69evahZsyaWlhYsXLRQ7kTw8/MjKCiQBQsWUqJECc27zpLi9vY4ODry+LEfMTExmsWCIAhavvwqA0RFfSDwZaD8e4mSJbLV06FSslQpypQtg4lGHu2/gYGBAbVq1ZLXaz/466906tSRBfPn4+XlRVRUlFoDzcjIiLJly6qlI/j5+TGgfz9atmyBc3knXCo4s337duLj4zlx4jg/9+1LBefyVKtahTq1azFz5owMe91Iu6ju2LGD5s2b0atXL5YtXUqL5s1o06Y1J04cJykpSfMmKBQK1qxeTf16dRkxfDie69cxa+ZMateqSZeffuLc2bM6G4yaj9/VpQLnzp0lODiIoUMGU6miOzVrVGfN6tXyBXb37l306d2bWjVr4FzeCXc3V3x9fYmPj2f//n10+eknKleqSI3q1WjSpDG7du2UA4LIyEg2btxIkyaNqVG9GpUrVaRdu7acOnlS5+MjrfF67uxZOnRoT5cuP7F82VJWrVxJ69atqF+vLp6enjr3MHj9+hVjxozmxx9+wLm8ExWcy7N4sQcJCQk8efKEadOmUqd2LWrWqI67mysjRgzH399f827gb/q8SJKEn58fI0YMp2qVysyZPZsF8+dTs0Z1Bg7oz507d7QChuy+fomJiaxZvZqePXpQrWoVnMs7MXLEcCIjI9m/fx91ateiSuVKdO7UiQcPtFdoevH8OcFBQRQvbv/ZvdmFbG2xtrbWajBLaRuuFSlaVGe6yT/NixcvmDhhIqNGjeTOnTuaxZCWInP1yhX69v2Z/JnsC/Fv5OfnR9myZSlevDgmJiZ8+vSJqKgPmtWIi40lOCgYR8cynxXkJSUlsW/fXsaPG0ubtm359deDtGzZKtP3SdGixVi8eAmTJk8m5M0b5syeTf9+/Xj69Klm1QzZ2RXH2dkZgPLly3Po0GGGDR9OlSpVyJcvH+fPn+PC+fPMmDlTbb6Ck5MTP/zwY6aPMyNWVlbkz5eP4FevxDwFQRCy5KsECmFhb9WW+7S0+GtZx+xwdHRk/vwFFLLN2ryIfxonJye6de8h/x4aEsLu3bsY0L8ftWvVpOOPP7Jm9Wq9Q9fm5mbYFCiAqclfjaZLFy/So3t3Htx/wPgJE7jmdZ3jJ05Sr359Dv76Kz179uTc2bNajT7SclynTJnM2jWrGTRoECdOnGTnrl0cO3YcR0dHJowfz86dO9Ua1Uqlkq1btuDpuZ6SJUuxYOECuRf29B9/kC+fNSNHjmDbtm1ajXFdjz8s7C2rVq2iabNmLF68BIVCgafnek6dOglAoYKFMDPLTe50F/zI9++ZM2c2cXEKVq5ciff9B+zavQeb/DYsXLCAjRs28OLFC2bOmI6NTX5+/fUgf3rfZ82atcTFxTFz5gxOnz6l8zm5ffs2U6ZM5t3btwwfNpwNaRMZL12+Qteu3VizehXTpk4hIiJC7XYmJqYUti2sNkk9JSWFc+fOsnbNatq0acv5Cxe5fuMmgwcP4fy5c8yeNUtrtRL+hs+LUqlk79499O7VE7tidly5eo3de/awe88eLl66jKNjGYYOGczevXvUXsPsvn6GhobYFrbFxCSX3COdkpLCyZMn+fPPP9n0y2YaNmqEr+9D1qxepdUwefX6NQB5ra3Vdpz+GuLj4wl5k3EQnVUxMTEsmD9fK70ps2Pb1m0AbNu6Tass/dHv574MGNAfH58HhIaEMHnyJK1gQalUcuLESVq1bp2lNLXjx49p/R1dx/HjxzRv+j8RHx/P/fv3adasOQYGBpiYmJAnb16e+D/RrEp4RASBgS8p7VA6WwG2KngeM3oUfn5+bN+xgx49emQrSDU2NqZLl64sXbYc+xIl8Pb+kwP796uNvGWFJEn4+/vz+PFj+X+Q0pZcvXbtGtOnz6BQIVu1EcCPHz9y9OhvPHz4MFujp+mZmppSuEgRgoOCtL7jBEEQdDGaNm36TM2T6T179pRzZ88CUN7ZmVq1amsNU4eFhXHk8GH595+6dMX2b2zsBwcHMXPmTI4cPsTxY8e+yhEeHkH58uWzdSEyNDSkXLlyxH+Mx8fHR7OYiIhw7t69y759e0lOTqaCi4taw9PKKg8NGjSkadOmBAYF8vLFCxQKBcNHjKB3nz7kz58/9QKaJw81a9YiNiaWmzdu8MDHhwoVXNSe87i4ODw8FnHyxAkGDBxEly5d5caYmbk5JUqU5M7dO1y5fAkXV1d5xZmYmBh2797Fq1evCAsLpXLlKvLa4paWVtjZFefK5cvcvHkDBwcHtSFwXY//5o0bdOvenTZt2vL8+XPOnDkDQJWq1XB1daVkyZI0b94Cd3d3rly+zMePH3ng84COHTvSsWMnzMzNMTIyolChQihTlFy+fJmQ0FBu37pFv/79adSoMSYmJhgZGVHMzo7YmFhu3LhOQnw8tWvX0WoEHD9+HK9r10hMTCR/fhuqVauGkZEROXPmpEzZsgQGBXLh/HkAKlepIr/+uXPnpmbNmrRq1QqFQoGPjw9v377lY3w806fPoHTp0uTIkYNcuXJhb2+Pn58f3t5/UqRoMa3Jht/y8yJJEqdOncRj0SKaNW/OqFGj1fZjMDMzw93dnbfv3rJr506KFC2Cg4MDBgYG2X79KlasiJOTE61ataa4XXFOnz7N69evSU5OZvq06Vjny8fZM38QFBRE/vw2NGrUUF6lJzExkTN//IGvry/t27fPcJO19O7evcuL58/5/vvvyZMnj2ax7NWrV/z666/ExaZuxFXc3j7Dz7LqNWnfvoPWa5ErVy5cXV2pV68+P/z4I63btKFVq9aZHmZmuTl39izjxo9j9JixWuWqo3XrNvTo0YPBQ4YweMgQevToQZEi6pN0AwIC8H34kI6dOpEzZ07u3r1LWGgojRs30dqs7NzZs9SrV59Zs2Zr/S3NIyYmVuf9fE26HuunT5/w8vICoFat2jx58oQiRYpQsmRJ+XYKhYIbN25QNe0zqnLjxnUePHhA167dspx6FBkZyS+bNvH8+XMGDBxI69Zt1D4X2WFgYICdnR1ubu48efKEkiVLUr1GDa1RLX3Cw8PZsX07OXPkoGrVqhgYGMhBwu3btxk9eoz8f104f55TJ0/i6OiIpaUlJUuW5M8/7zF+/HgeP36MtbU1BQoUyDStTcXQ0JCHPg/588971KhZgzJlympWEQRBUJO1b7Z/OHNzCypXrkzVatW/2lG6VKkMGxb6mJqaMn7CBLZs3UbDhg31Do3/8ssmli9bpjPH1djYWL5QNG3WjIYNG2ldhExNTenYqRMlS5UiNCSEnTt3qOWcXr58id+PHsWueHEaNGig9b/Y29tTs0ZNFAoFVy5flvPqLSwsqFa9BgDu7hUpU7aM2u1UF0WFQsGdO3d05uOnf/xlypSlcuUqGBgYUKduXSZPmcKEiRNpo7GPhIWFBdbWqbepUqUK9erV17r4qSa8hoaEUKFCBa1Vf4yMjChRMjVwCQ+P0JlCVK1aNWwLF8bKyopKlSqpBWqWlpbUqlUL0nbYfv9eu8fN2NiYPHnzQlqjrGPHTlqr2VhYWsqPIzDw5Wf3/n2OZ8+esWHDBhQKBU2afK8VKJH23mnS5HsUCgVbNm8hKG3XXpXPef3ypXsOqlarhk2BAlhYWDBo8BD69OnLqNGjKVTorwa4JEmkSKmjama5dX9GvsSzZ095HxHB0GHDSJFSGD9+HK9fZ20df10sLS2xsbHR+hz9HeLj47ly5Qo9evbU+Xr+f5A3b15cXFzUzjmULs3bd2959+6tfC45ORn/x/6UKVNGK6DT593btwQEBNCvf3+aNW/Oq1epI1mfS6lUsmfPbpKSkli6bCmdOnXK0vsiKiqKLVu2MGP6NJo2a0ajxo0xNDSUU6H8/f0ZNXo0VlZWkBaQNGjYEIVCwYjhwwkICMDY2JiWLVvh4bGYwJeBDOjfj3379uocPdXFyMiIXGnBWkhIxgtuCIIg8K0CBV2N32/J2tqarl270bdv36921K1XL0tf/roYGhpStWpVVq5azeUrVznw60EmTJxI7dq11QKHffv2cuFCau+1PkZGRloNZhU7OzsqV64MgNe1azx//hzSeuKuXbsGQLGiRSlQoIDa7UhrDBZO67UMCgqUXzMjIyN69erF9Rs32bJ1q1qOrKpc1VhJSMx8GVjHMo7yvA0zMzO6dOlK9+495IuhLmXLlsPc3FzztJrq1atnuFeFPu7u7hw9+jtnz52nyfffaxbLr09qDr72/I30HBwcKZkWEHyJr/V5kSSJCxcu8OL5c5ycylO0qP6lIwsXLkyZMmV58sSfy5cv621ofM7r5+LigoGBAQYGBjg7OzN6zBgqVaqk9j5OSEjgTVrqkVUGIwOfIz4+nhs3blC9Rg2cnZ1p1qw5FSq4MHDgQM6eOaMz7e+f7MOHSJo1a6oVkP5/Urx4ca3vW+t8+bArZsetW7fkcxER4fj4+ODuXlFrDwl9ChQsSNWqVeXvrXnz5tKrZ0+tNKysHn1692blihVMnjyJ16/faKX+pSdJEiEhb/Bcv54WzZvx7NlTZs+ZS4kSJVCmbabWvn07jv1+jBw5c7J+3Tr574wbN5alS5ZgZmZG2Nsw1q5dQ2xsLKSluc6aPZtSpUrjde2afF4QBOFr+yqBQr581jg5lZd///BB/2o/GUlJSSE2NvZfdyHPiImJCU5OTnTv3oP/a+9Ow5q6tj6A/yEgYBRkaiVBsb6KaAextJdJK2qrdaj0fdrrrFWLRdS2ToVasaPtfUFFRRHUihP2ihXbOoECKlatbemFCCiCjFr0IgkgCYkZ3w8hKclJIAnQol2/58kHOScxyT7nZK999l4raecupGecwZv//Kd2e1ZWlsUXeXt7e/j4qG8di0QilJaqF9Xx+XUou6UOGpqbxTh8+DD27NnDeFy/ri4Q19j4ACKRUPu61tbWcHR01E5VampqQmFhIbKzsrBv3z6Ulpieg9vBwYHRAWiPq6uL/p8YOtK57Nmzp7aCrUwmQ3l5Oa5cuYIDBw7gxx9/1N/dKDa7JxwczK+E21Xni1AoxM2b6gXUzs594OhovDPfWn5+HoTCP9q/NUva768e9b516xYuX7qE8ePHw9HRESwWC7NmzUKAfwCio9di3759Bhfxd1ccDhdc7p9XjK6ryWQyFBQU6CzoN4TFYsE/IABnMjK061tuFt/E77/f0Q6QmKtHjx6wtbHFtOnTdDJhTQ0NRV0dH2s+Wqv929b4beB6eoLr6alTqG1rfDx8fX0xaeIk+Pn56f8XOqysrMDL52Hv3mS8OnEioqPXaQM+FosFb+8h2vUNPXr0wOiQEAwf7ou35i9ATEws1kZHI2LJEowbq7473Xra78CBA7Fo0SL09fCwaNCEEEJM0UmBghv+Z5B6HjsAVFVWGR2hbEt1dTVWr1qJ6upq/U3dnqolRaehqTitubi4YNmydzF27FgAQGVlZYcWlbW+QyEQqDOECIUi3L9f22ovwwYP9saKlaswafIkRodXKBTi2LE0vDVvHgID/LFixXKcTj8NWNCu3Y1CocCvv/6KyMgPMDI4CDNnTEfynj1obGjQ37VLdNX5IhQ24X6t+ZlMmkWidu8MPSrEYjHS0o4iMCgIo0eHaP/u4OCAxRER8Pf3R9ymjYxF/I+b7raYWaFQorCwELExMXhn0SKIhEL0699PfzeGYcOGwd7BATk5F/Dw4UNcvXoVwSNHWpwetDPZ2NoypoQaMn7CBESvW4eIiCWMqag+Pj7Yv38/Ug4dwsKFC+Hn5wdrFgsrlr+PjPR0oCWAmDxlCsLCFjGC8JdGj8aSJUu7bH0JIYS0f5UzAZvNxosvvqj99+07t9Hc3Kyzjymam5thY2Nj8SKzv9LDhw+xeXNcm3nQNdzc3DB1qnqOd2lJCRq6sIM62Hsw5s+fz5ha1foxa9ZsnYWh+fn5eGvePHy8bh169+6F1CPf4syZs9i0KQ7zFyzAYO/BOv9HW+zt1AuNuwuBQIDo6LVYMP8tXL9+Hes+/hg5F3/E13v24N333sOoUaP0n9Lpuup8kclknT5Sbm77ubu7w85AutY/g3ru+DcouVmCsLBFjOlrbm5umD1nLtzd3ZFy8ADy8v7IPPW4mTLlNZ0Rc2OPKVNe039qp5JIJKit/S+uXv0Jq1augKOTE3YkJiIgMNCk48rR0RHjx4/HsbRjyMrKxJWfriBkdAijw9ydsVgsvPbaVINTx1gsFjgcLiPg8PX1RVDLeikAePbZZzFgwACdfdDyfFdX1zbrzBBCSEe0GyiYOuoWEBCAES2VYq/+9BPKy8v1d2lXRUU5PDw4jFGX9ggEAhw6lMKYWtORx8WcHJM/e2vt1TXQ4HC52rnfHdH6PWqm0zg799FOVaivr2/3Lkdr5eXliI2Jwc2bxZgxYyY2bNyEp59+mvFDZipHJ6dOT31pKbFYjB0JCThx/Diee2444uO3mZQ/vSt0xfnSp48z3N3VnRGRqBlisWnBR08222inzdz2c3Fx1R6HbbG3twe3JdNWZ9zJUalUyMhIR0Z6OiKjonSy57Q2YsQITJjwKu7fv/9YBwrdha2tLbhcT3hwONi4KQ7h4eFmd/IDAgLh6uqCqMhIPPnEExju66u/y99abm4uFoWF4dKlSxQsEEI6Xbu9P1MzI3h4cDB9xnSgJf3bmYwMs0Y3hUIhLl++jICAALNHJIXCJuTm5uKXn6922uNWWZlFgULBtQKTPreNjQ0cevbEYG/vNtM8tkWTAQQto9TPPvssAMDZ2QXeQ9QZgu7X3odQaHwNROt57gqFAqdPncK1azz09/LCG2++adKPOo/Hw+lTp8wKSP4KPB4PJ04cBwCEvh5q0vSFuro6pKYe7tD0MEO64nxhs9kYOlSdY1/ULIJEYjy3e+usQ0OG+DBG37ualZUVrK3Ulx9Rs0h/s1nUtRtO4dTJk4jdsAG+bXQke/TogZAxY8Bms82+zhDzsVgshIaGYv36LzFy5EijiRna0qdPH4x4Xr0WgOvp+acfq5ZqampC/NatjOle7T1OnjyBwsJCrFyxgrFN/7Eo7G2sWfMhCgsL8PnnnyE3N1f/beiQyWR40JINjsMxvgibEEI02g0UTGVlZYVx417GjBkzAQDffnsEmZlnTRrhUKlUyMm5AKlUin/4++tvblf//l7YvHkL47Z6Rx4LFy60aIFY9rlslJa2v9i3uqoK1VVVePrpp9G3b1/9zSaprf0v8vPzAQDBI0dq6x3Y29tj3LiXwWazkZ+fh6JC9aJlQ4qKivBhVCT4fD5kMhkELQtr+3l6Gkw/KJPJUF+vWy31zp3byP0t12BgpVQoTDoG/gx8fh1EInWn1Nt7iMFOC5+vu7BYKBTiXHa20cW+luqK84XFYmHM2LHw4HBQWlKCqkrji0XLbt1CaUkJPDgcjBo1yuB3AQvaT6lSmrS/nZ2dtrqwqYMRhohEIuxISACfL8CmuM0mBX++vr5YtXo1Jk2apL/psdHZaxRUKhXOZWdj6ZIIfLl+PQQC0xfgu7m5wd/f3+gx1hbNnaKDB/Zj/IQJSD99Gls2b9aex91Z7969sWDhQnz62WfYnrCD8Rtj7DFlymt45plnELd5M2Ob/mP313uQmZmFwqLryMzM0pnSaIhcLtcG5m5uHb+jTQh5/HVaoICWBYNLli7Fa1OnQiQS4asvv8Tp06fazGKkUqnwyy+/IHlPMmbPnvNIrk9o7W5NDeK3bjFYkVdDKBTi3PlzYLPZGDd2XJuj9rm5uQYXdysUCqQdTcO1azx4cDiYO3eeznfn5+eH0NDXAQDHj/9gcERcLBbjh++/R2BQENzc3MBisWBvp56Gc/fePYPPuX79OvJbpmwoWjqRCoUCTo6Gp6jU8evMrlraVVrn66+oYE71qaurw89XfwJadXhVKhXs7e3BNmE6jbm64nzx8fHRBh9nM88aDHA0xx8AzJw5S5s5yxBz28+cNTcDvNSpd+sFAovuRt29W4OTJ09g+owZZlXYtbe3N1j/4nHS2WsU7t27i+TkZOTk5ODf//4GJ06cMCkg7AiVSoWM9HQkJiZi7dpoxMZuwDvhi3HoUArWr//C4PWpu+nduzc8PDgGr41/BU3F8v5eXo/18U8I6TyMysxSqRSFhYUoLy9HdnY2Ll+6pJ13L5crIBQK0SwSgS8QwNHRkTHq7uDggMDAQFhbWYPHy8fp06dRVV0FLtcTLi4uOnPdhUIhUlNTkZi4A6tXf6CtUvko0lQaFdTXw9a2B44dOwYHBwdwuVydKQ4CgQDb4uORlnYUy959D6Gvv86Y/695raKiIlhbWyPvP3kYNGiQtgKnWCzG17t3IykpER4cDqIioxAUFKTz3dnY2OB5Pz+Im8U4fvwHlJaW4KmnBsLV1RXW1tYQCATYvWsX5HI53g4Lg62tLVgsFvo4O+Py5cu4XV0NuUKO554bDgcHB6hUKhQVFWHf3mRMmjwFvPx8SCQP4TVgAHJycuDj4wMOhwMej4fs7GxkZ2ehoaEBcrkCEokEEokEIpEIzs7OOp+3vLwcBdeu4fiJ48jNVRdwUymVUCqVEIvFcHJyQllZGXj5+UjPSEfxjRtAy0iyDcsGUqkUbDYb169fx2+/5eLsmTOoqKgAn18HqUwKaytrKJRKODs7w8XVFbfv3EZZWRn4fAGG+PjA3d0dVlZWEAgE2L59G7yH+ECpVKLg2jUMHDgQd+7cQeODBwgKCkZxcTEuXsxBRno6amtrIVcooJDLIZPJYGPDglwuB4/Hw8WLF5FzIUd9B6O5GTKZXPs+9TuznX2+aKqDW8EK33xzCI0PGuHtPRi9eqlzzt+vrUVCQgIyMtIRvjgCc+fO1Z7D9fX1ZrWfQqFASUkJePn5OJp2VFvHAwDE4mY0NjaiZ8+ejM+sIZXJcOHCefToYYvRISEmTQVqXZm5X79+eOaZZ8xe02RIW5WZLdXQ0IAffvger7zyismVp01lqNoxWlVm9vDgmJRC1Njr6BMKm5B5NhP37t0DWqa5BQePNKnNDNGvzNw67Sdajq3vv/8OaUfT8Nlnn8M/IADW1tYYNmwYbG1tkZJyEBdyLsCT6wnPfv0Y11BjGhoacPbMGYx4foROm5SWliAvL0+n4rex96j/HatUKlRWVsLR0dHk99EWU9vEEpqK5f379cPU0FCj5yYhhGhYPZTKdIaFGhoaEBX5gfYCacyQIT7YFBdnMBMDWkaDbty4gZ07k5CdlQUAcHJywpAhPrC1tYFE8hDFxTcwOiQEy5YtYxT2etRIJBLExsaAy/XEjBkz8N13x7B//37cranB0KHD4OLiDJlMrs1zH744AtOmTTP4Q6B5rSOpqZg2fTqmTg3F3r3JKCsrwxPuT+DmzWLI5XKMnzABERER4HCMF9aSSqXIyszE7q93o7REXWcBLT/0s2fPwdthYYyOVnFxMRITdyA7K0vbZk1NTeBwOVi+fAX69u2L3bt2YdeunWCz2Zg7dx7eDgtDcXEx5s6ZrfNarU2bPh2RkVE6nzkpKQnbt8Xr7KcRHByMzz//Ajt37cSR1FT9zUDLa4a/E46PP15n9Jhd9u57WLx4MQCgsbER+/ftQ2rqYTQ2NmL4cF/Y2NigubkZ4eHhGDN2LM6fO4eY2BjcralBSEgIIqOioFSqsGrlSm376YuJjQWHw23z8x9MOcSoJq3R2eeLUqnEzz//jKTERPz2m+685ZCQEMx7az5eeOEFnY5NXl5em+9fv/1aH6fGtPWZ6+vrsebDKFTfvo0tW7aa1JlOSkpC5tmzbV57LKH57G29X2MkEgmKitTT+zy5XNjZ20OpVOJIaiq2b9+GmNhYTJ48Rf9pHZKUlIS8//yGmNgNOmucNNfvEc/7aY/5tui/TnNzM+zs7BiL21UqFc6eOYONmzaCxWJhgJcX/i8m1uL1VZpjBwDjmiCRSLBv3z7w6+oQsWQJXFx066pIpVKkpKRgZ1IiRCIRgoODMXPmLDzv58e4w6avsrISq1auxMK3F+q0yalTJ5G8J1nnuDL2Hlt/x+Hh4cjOykLc5jgsXboUkyZNZgTv5tJvk8504fx5LFu2FIsXRyBiyRJGOxNCiD5GoNDZVCoV+Hw+iouLUVpaqp1W4ezcB0GBQXiyb98OX1i7A5lMhvPnziEoOFi72E4ikeDGjRsoKCjQTq3geHjgH/7+cHV11XuFP+gHCpGRUbCzs0NTUxOqq6thY2OD/v37m5RdRkOpVKKhoQFVVVVwcHBo9/mqlroQ1dXVkMlkeOqpp+Dk5KRtK5VKBaFQCBaL1ebrdFcSiQQ1NTXg8/ngcjl48sm+Oj+aEokEUqkUvXr16pRRQlN19vmiaSdNwSp3d3f06tXLrNfoKiqVCgcOHMCG2BiTO9NJSUnYm7wHPj5DYW9v2Wi2IUKhCDxePjZu3IRXJ07U39wmTZudP38OaUfTUFhYoN3m7u6O+G3btYkGOouxzmRHAgWBQIB10dGYPGUypk+fYbQTWVlZiYSE7Vi7NtrijqyxTvidO7eRkJCAia9OxMhRo4yee0qlEtlZWdgavxWVFRVAS2A9fsIEvPPOO/Dw4KCpqQl7k5NRVPRHympNwN2/vxdcXJy1fxcI6lFdXaVzXCmVSlRWqaeQDvDy0r4XzYCPs4uLduCmsbERHhwOvvrqX+2uE2iPsbbtKIVCge3btuGbbw5ha/w2BAQE6O9CCCEMXR4oEPMZChQM3Xkg5FFXUFCA995dhjFjx5p0nHf1HQVTAxZjJBIJDh8+jMQdCRCJRFixchXmz59vtNNtCZlMhs1xcSgru4W35i/AkSOpELfU4WjdieVyOPpPZfi9pgb1AgG8vYfgzu93cLemBmw2G+8vX240WMjNzcWJE8fx4YdrLJ66oh8oqFQqfPfdMSiVSrzxhmnZ1tCSjnrLli0QCYVY89FH8PTULeLW1NQEobAJbm7u3WadQFtUKhUSd+wAj5ff6YHC/dpaREZGwtHJEV98sb7duy+EEAIKFLonChTI34VUKkXcpk248tMVxMVtxqBBg/R30ZGSchAsFgtTp4Yypsx1RElJCSorKvDS6NEdPtc0mZgCAgMRFBRksLPdERKJBDuTkuDB8cDrr/8vHjx4oC28Z2wEvrNo7gJZWVlh3rx5+ptNJpFIcOxYGkJCQtCrV2/8fPUqAoOCLEp9KpVKtetnHnWatnVzd8Mbb7zZ4WOxtazMTCxf/n6Hg2FCyN8LBQrdEAUK5O+kqKgIy5e/j9CpoTRvupurrKzEv776Ems+Wtupd3RI13rw4AE+/fQTKBQKfPLJp4x1H4QQYkzXDj8Rs8hkMggEAuTl5aGyQp0Dv7KiEnl5eRBYmEKSkO7Ox8cHM2fOwtnMszqZk0j3IhaLkXLwIEa99BK8WlLbkkfDjz9eREFBAebMmUtBAiHELHRHoRtpL+uMJRlZCHkUiMVibNq4EXKFHFFRH5o8R538eU6ePIH8vHysWr2a2ucRUl5ejui1azHu5Zc7fb0MIeTxR4FCNyKTydqsOMpmsx+JBXmEWKKurg6ff/YphvuOoA5NN6QpsKhf84B0X5pzaujQYViwcCFNYSWEmI0CBUJItyEQCLBx4waMCRmDV8aP199MCDGRTCZDwvbtcHRywpw5cxjFUQkhxBQUKBBCCCGEEEIYaDEzIYQQQgghhIECBUIIIYQQQggDBQqEEEIIIYQQBgoUCCGEEEIIIQwUKBBCCCGEEEIYKFAghBBCCCGEMFCgQAghhBBCCGGgQIEQQgghhBDCQIECIYQQQgghhIECBUIIIYQQQggDBQqEEEIIIYQQBgoUCCGEEEIIIQz/DxHZNop7xDX+AAAAAElFTkSuQmCC"
    }
   },
   "cell_type": "markdown",
   "id": "b3a81fdc",
   "metadata": {},
   "source": [
    "![image.png](attachment:image.png)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "id": "d1fe461b",
   "metadata": {},
   "outputs": [],
   "source": [
    "#计算IC值\n",
    "def calculate_factor_ic(data, factor_column, return_column):\n",
    "    \"\"\"\n",
    "    计算因子的 IC 值（Spearman 秩相关系数）\n",
    "    参数：\n",
    "        data: 包含因子值和收益率数据的 DataFrame\n",
    "        factor_column: 因子列名，如 '因子_ZScore' 或 '中性化因子_两步法'\n",
    "        return_column: 收益率列名，如 '收益率'\n",
    "    返回：\n",
    "        ic_values: 各截面（按日期分组）的 IC 值序列\n",
    "    \"\"\"\n",
    "    ic_values = []\n",
    "    # 按日期分组计算每个截面的 IC\n",
    "    for date, group in data.groupby('DATE'):\n",
    "        factor_values = group[factor_column].dropna()\n",
    "        return_values = group[return_column].dropna()\n",
    "        # 确保因子值和收益率值在该截面有对应数据且无缺失\n",
    "        if len(factor_values) == len(return_values) and len(factor_values) > 1:\n",
    "            ic, _ = spearmanr(factor_values, return_values)\n",
    "            ic_values.append({'DATE': date, 'IC': ic})\n",
    "    return pd.DataFrame(ic_values).sort_values(by='DATE').reset_index(drop=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "id": "6ba6feec",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "因子_ZScore 的 IC 结果：\n",
      "        DATE        IC\n",
      "0 2010-01-11 -0.019883\n",
      "1 2010-01-12 -0.140104\n",
      "2 2010-01-13 -0.176098\n",
      "3 2010-01-14  0.063184\n",
      "4 2010-01-15 -0.200439\n",
      "中性化因子_两步法 的 IC 结果：\n",
      "        DATE        IC\n",
      "0 2010-01-11 -0.027072\n",
      "1 2010-01-12 -0.143014\n",
      "2 2010-01-13 -0.172297\n",
      "3 2010-01-14  0.063153\n",
      "4 2010-01-15 -0.197900\n"
     ]
    }
   ],
   "source": [
    "# 计算因子_ZScore 的 IC\n",
    "ic_zscore = calculate_factor_ic(data, '因子_ZScore', '收益率')\n",
    "# 计算中性化因子_两步法 的 IC\n",
    "ic_neutralized = calculate_factor_ic(data, '中性化因子_两步法', '收益率')\n",
    "\n",
    "print(\"因子_ZScore 的 IC 结果：\")\n",
    "print(ic_zscore.head())\n",
    "print(\"中性化因子_两步法 的 IC 结果：\")\n",
    "print(ic_neutralized.head())"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d548ed07",
   "metadata": {},
   "source": [
    "## **九、两个因子IC值序列t检验**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "id": "40c907d2",
   "metadata": {},
   "outputs": [],
   "source": [
    "def ic_ttest(ic_series, factor_name):\n",
    "    \"\"\"\n",
    "    对 IC 序列进行 t 检验，输出统计量与显著性结果\n",
    "    :param ic_series: IC 值组成的 Series（如 ic_zscore['IC']）\n",
    "    :param factor_name: 因子名称（用于结果打印）\n",
    "    \"\"\"\n",
    "    # 计算统计量\n",
    "    mean_ic = ic_series.mean()          # IC 均值\n",
    "    std_ic = ic_series.std(ddof=1)      # IC 标准差（无偏估计）\n",
    "    t_stat, p_value = ttest_1samp(ic_series, popmean=0)  # t 检验（原假设：均值=0）\n",
    "    \n",
    "    # 输出结果\n",
    "    print(f\"=== {factor_name} IC 序列 t 检验结果 ===\")\n",
    "    print(f\"IC 均值: {mean_ic:.4f}\")\n",
    "    print(f\"IC 标准差: {std_ic:.4f}\")\n",
    "    print(f\"t 统计量: {t_stat:.4f}\")\n",
    "    print(f\"p 值: {p_value:.4f}\")\n",
    "    \n",
    "    # 显著性判断（95% 置信水平）\n",
    "    if p_value < 0.05:\n",
    "        print(\"结论：IC 均值显著异于 0（p < 0.05），因子有效性通过检验\\n\")\n",
    "    else:\n",
    "        print(\"结论：IC 均值未通过显著性检验（p ≥ 0.05），需谨慎判断因子有效性\\n\")\n",
    "    \n",
    "    #补充：IC序列分布分析\n",
    "    positive_ratio = (ic_series > 0).mean()  # IC 为正的截面占比\n",
    "    print(f\"IC 为正的截面占比: {positive_ratio:.2%}\")\n",
    "    print(f\"IC 序列中位数: {ic_series.median():.4f}\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "id": "b2d98bef",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "=== 因子_ZScore IC 序列 t 检验结果 ===\n",
      "IC 均值: -0.0333\n",
      "IC 标准差: 0.1384\n",
      "t 统计量: -12.9881\n",
      "p 值: 0.0000\n",
      "结论：IC 均值显著异于 0（p < 0.05），因子有效性通过检验\n",
      "\n",
      "IC 为正的截面占比: 38.64%\n",
      "IC 序列中位数: -0.0373\n",
      "=== 中性化因子_两步法 IC 序列 t 检验结果 ===\n",
      "IC 均值: -0.0333\n",
      "IC 标准差: 0.1382\n",
      "t 统计量: -13.0022\n",
      "p 值: 0.0000\n",
      "结论：IC 均值显著异于 0（p < 0.05），因子有效性通过检验\n",
      "\n",
      "IC 为正的截面占比: 38.95%\n",
      "IC 序列中位数: -0.0376\n"
     ]
    }
   ],
   "source": [
    "# 对两个因子分别执行 t 检验\n",
    "ic_ttest(ic_zscore['IC'], '因子_ZScore')\n",
    "ic_ttest(ic_neutralized['IC'], '中性化因子_两步法')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "35664257",
   "metadata": {},
   "source": [
    "## **十、分层回测以及绘制cumulative sum IC和分层回测的图**"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0ce1d5a7",
   "metadata": {},
   "source": [
    "### **1.cumulative sum IC**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "id": "44168bfb",
   "metadata": {},
   "outputs": [],
   "source": [
    "def plot_cumulative_sum_ic(ic_data, factor_name, save_path=None):\n",
    "    \"\"\"\n",
    "    绘制Cumulative Sum IC曲线（累计IC和曲线）\n",
    "    :param ic_data: IC值序列（DataFrame，含DATE和IC列）\n",
    "    :param factor_name: 因子名称（用于图表标题）\n",
    "    :param save_path: 图片保存路径（可选）\n",
    "    \"\"\"\n",
    "    # 计算累计IC和\n",
    "    ic_data['Cumulative_IC'] = ic_data['IC'].cumsum()\n",
    "    \n",
    "    # 绘制曲线\n",
    "    plt.figure(figsize=(12, 6))\n",
    "    plt.plot(ic_data['DATE'], ic_data['Cumulative_IC'], label=f'{factor_name} Cumulative Sum IC', linewidth=2)\n",
    "    \n",
    "    # 图表设置（参考研报图表风格）\n",
    "    plt.title(f'{factor_name} 累计IC和曲线', fontsize=14)\n",
    "    plt.xlabel('时间（交易日）', fontsize=12)\n",
    "    plt.ylabel('累计IC值', fontsize=12)\n",
    "    plt.grid(True, linestyle='--', alpha=0.7)\n",
    "    plt.legend(fontsize=12)\n",
    "    plt.tight_layout()  # 自动调整布局\n",
    "    \n",
    "    # 保存图片（可选）\n",
    "    if save_path:\n",
    "        plt.savefig(save_path, dpi=300, bbox_inches='tight')\n",
    "    \n",
    "    plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "id": "a46eda5b",
   "metadata": {},
   "outputs": [
    {
     "data": {
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j0+KZ/lyd5rV8+XIzgunCCy/M8bFdK8HpSKalS5dKYbjyyiu9nk+lx6xFGS0a6dRApeeixbJLL700W7FQpzdqjvU5UDrFTPPsuowYMUIKkxbttGCpq7xpY24dHXbeeeeZVQE9aZN4LZ7p8/r0009L27ZtzXYtRAEAEKhY5Q0AAIdwFU/0Q7irn1BOzj//fK/vs05LOpm8rvaVGzq1SUcKabHr+++/z3Z7y5YtzUULCNqvRqcS3XLLLWY0jk6h0iKKFi703LUIoFP7brrpJlNc0pW6dOrSm2++aYptWkhR+hhawND+Ulpk6t27t/z111+m4KHb87oqmx7b77//bgpIOrKmcuXK8tlnn5nl5PM7Gsw1mkpH79x8883mGLWI5Brlo9O4tLCiUwUXLVpkRqBdcsklpvBxspxoAUSPS1e4GzJkiBQGnY73zTffmBE9OtrqjDPOMD9Xp+ppsU9fK1fRRUee+ephlDWjOs1MXyMXfc1dqxgWNC1U6nRDLVbqz9YCn/ZF0txcd9117gKX9mH69ddfTXZ15bcnn3zSjFTSaXR6raPLNKMAAAQcf3cFBwAARUNXXsvvylaPPvroSR9bV0576aWXMkeMGJEZGxtrLgVp6NChJz0+z1XofvvtN7OiVnR0dGbZsmUzu3Tpkjl27Nhsj/nrr7+aFe70edHVwXR1Ol15LesqeLpCnK6UFh4ebq5ffvlls92Ta5W3U9EVwS6//HJzXCVLlszs0aNHjqvC5cbatWvNCnH6s88888zMuXPnmu2bNm0y23788Ufz/cSJEzO7devmXvXt448/zkxJScn2eLoKX0REhNnvrbfeKtRV3pSu0KaZqV27tnl+mzdvnvntt99m2y8hISHbY2Z1//33+1zlTVeT83TXXXcV2Cpvuiri//3f/2X+/vvvmYmJie7t+jpoZvWcdOW/MWPGmO3bt28356r/f2gO9PH0uAEACETF9D/+LmoBAIDCp42DtW+SjlbJi3bt2pn7nGpUk4720d5LOgVIp1/de++9p3nEOBkd2aOvi666pyvf6QpuOhpJRz3Nnz/fTH3TJtCeq+Hp6J277rrL9EXSUU2uaX0uOgpMexvpFDqdFueL3t64cWPTDNtf56051ilk2kw766pt11xzjdeqgHrR6YauqZ36nOk0Rt0/p15cvvz999+meb2ujJh16l1WOu1SR4vptD7t/+Tq26V09Jj2XtLXSKdw6r4lS5bM47MAAID/MeUNAAAH0L8fZWRkmA+2WgzIC/0grh/eT0WnLyltAp3bZedzs5KcNpZ2LRWP/+hUPW0yrtPndDUyF53apsUkbfiddRUxLXIsWbLEZzFJaYHFtSreyfpZ6Wpr/qLT41RiYqJXQUlXUtOLJ+3D5OrFlPX+rlXecsvVhF1/7qno9D1t3l66dOlst+n/H3PmzJGFCxeaFfd0WiIAAIGIEUoAADiEjtTQ0Sx6sUVuCk/aCyk/y8I71YEDB0zxsHz58v4+FAAAEMQoKAEAAL/RVcRORUeS5HVUFQAAAAoXBSUAAAAAAADkyYn1WAEAAAAAAIBcoqAEAAAAAACAPKGgBAAAAAAAgDwJy9vuOBVdVWXnzp1SsmTJXC+ZDAAAAAAA4G/aZvvIkSNStWpVCQk5+RgkCkoFTItJNWrU8PdhAAAAAAAA5Mu2bdvMSrsnQ0GpgOnIJNeTX6pUKQkkaWlpsnjxYmnTpo2EhREN+A9ZhE3II2xCHmET8ghbkEXYJC3A83j48GEzSMZV2ziZwDs7y7mmuWkxKdAKSjpdr1GjRlKmTJlTDm0DChNZhE3II2xCHmET8ghbkEXYJCNI8pibFj7FMnWCHAq0mle6dGk5dOhQwBWUAAAAAACAcx3OQ00jcMtlKHDp6emyevVqcw34E1mETcgjbEIeYRPyCFuQRdgk3UF5pKAENx2splVIBq3B38gibEIeYRPyCJuQR9iCLMImmQ7KIwUlAAAAAAAA5AlNuQEAAADgNOn0ltTUVH8fhmNX1VJJSUkBuaoWgkuapXkMDQ2V8PDwAn1Me84Ofqcd6OvWrRvQnegRHMgibEIeYRPyCJuQxxN0Wsvu3bsdM8XFRvq8lyhRQrZu3ZqrlakAp+YxMjJSKlSoUGALiFFQgpv+MlCxYkV/HwZAFmEV8gibkEfYhDyeoIWkgwcPSmxsrBQvXty6D5AAkJmZaUZQ6vvVjh07zLaCKCpRUILXMN0VK1ZI8+bNzXA4wF/IImxCHmET8gibkMcTH9Li4+PNBzP9qz/89zokJiZKdHQ0BT34XaaledTjKVmypGzfvl0SEhIKpKDk7PGp8Bl8hurC38gibEIeYRPyCJuQxxNFNb0U1PQR5F9GRoa/DwGwPo9a4CpdurQkJycXSM83CkoAAAAAcBrNd21qvAsAJ+NqzK3F8NNFQQkAAAAAToNN01oAoKjerygoedBhXyNHjpSGDRua+YVt27aVyZMni1Po3PfGjRs7dg487EEWYRPyCJuQR9iEPAb/6CttNp7XS1Y6LdI1kqswRUVFFfrPAHIryiF5pKD0Lx3udfHFF8tjjz1mhqwOHz5cIiIiZMCAATJlyhRxSqWyTJky/IUFfkcWYRPyCJuQR9iEPAa3SZMmSdmyZfN80QKSp169epkpNpqTU10uv/zyfB2r3lc/w5FF2KCYg/JIQelfH3zwgfz222/SrVs3Wbx4sbz00ksyc+ZM6dSpk1x33XUF0rDKdvqXg/nz5xfJXxCAkyGLsAl5hE3II2xCHp3RZ0WbrnteNm7cKO+8844ZjeS53fVHeNf9XMaNGyd79+6VAwcOZLvs27dPnnrqKXOfnj17yp133pmnY/zss89yLE656Oe4xx9/XGrUqCExMTFmwMC2bdskEM2ZM0c6duxoRr+0bNnSbwMfNm/ebJ5jvQ7kn3Eye/bskSuvvFLKlSsn5cuXl1tvvVVSUlJydd/MzEw5duxYgS1YcO2110rr1q193rZ27Vo566yzzAyrBg0ayI8//ihFiYLSv9566y1z/eabb0pkZKT5Wofv6pvPli1b5K+//hInKIjGXEBBIIuwCXmETcgjbEIeg1fWwpDLhg0b5LbbbpOQEN8fJbM2KI+NjZUKFSqY0WyeF/2Mdd5558knn3wi//vf/0xxRP+YnxfnnnuuKWrOmzdPpk6daq71MZo3b+7eRz/Pffrpp/Lqq6/KDz/8IOvWrZNrrrlGAs369eulb9++0rRpU5kwYYKcccYZMmjQINm5c6cEGi1GaiHR1xRJl6pVq5rXVq/9sULbhRdeKNu3bzeZGTVqlHz++efmOrcyi2D1Sy3IuopJv//+u1x66aVmlN/ChQulqLAcgYipmK9atUrq168vrVq18rpNK+U69U17KfXv399vxwgAAAAARcWzMHT06FHzR3ctMul2/cN7yZIl3UVF7UWrcttP6+GHH5YXXnhBbrzxRlMcKVGiRL6OUUeO6MU1ImTlypUye/Zs8+HaRQtWDz30kGlvovRY9Wsd+VK7dm0JFE8//bQ5Xj0fLeZ1797dnOfrr78uzz//vAQSLSSNGDHCjLzR4qIv+hm8ffv24g+rV6+WWbNmmcKM9lVWy5cvN4XJJ598Umzx2muvmRF4OipJR9/p9NK///7b/L/1/fffF8kxMEJJRHbt2mWuXWHJGuSaNWtKXFycH44MAAAAAPxHpzRq8Ug/F+kUJB0RoUUk19QyLTDVrVs3T4+pI4muvvpqef/99/NdTPLlgQceMMen09qUHqcWL+Lj4937nH322TJ9+nRTiAoUOmJm7NixphDmGhmm1+3atZMVK1b4+/CCjo78UZ650aLkN998Izb5+eefzSg1LSa5dOjQoUgzQUFJRA4fPmyuK1Wq5PN2bS63Y8cOCXb6F4UqdRvJ9wt2yNBP5knC0RN/aQD8kUWdF86qMbABeYRNyCNsQh6dQQtGOk1Mp6jpH+J1dJH2atGv9aL9iLS3T1babyannjM62snXKliuleV0RFRe/fnnn6ZQ9OKLL7q3aTZ1lsnLL79sRpbo5z4tYHXt2tU9wsrV56lFixZm6lCzZs3ku+++83psPU+dTqT31c+MWlzw7B3m2e9HRxDpY918881ej6FT8nSamv6MJk2ayLfffpvrc9PnXo9dV1X0pCuU66JSSkf76MWTTivTGTdKj0/3r1WrllSvXt2MbtKpgdojSM/ftc8///zj9Rg6Kkp7VeVlat7AgQOldOnS5rnS58HVqN3V86pOnTrme73W713HmJseSnpOjRo18tqm56IFT+3L5SrA6Ygu7Zulr7NmQHt/5ZYW6qpUqSJDhw6VL7/80hQmq1WrJp07d3bvc7Ln6rPPPjPP7aOPPirFixc30+c++ugjMxpLH/vQoUNyunRkkvZPypqJO+64w7TxKSpMefMYmulZ2cv6hrd//36ft+mQSdcQT8/ilL7BuN5ktHqsFw22Xlxc2zWgnnMsc9qux6nBzdr40HX8Weew57Rd/1HQx/Xcro+rP/Pr+Tvlg+kn/qf9ctYmuaN3A/M4OR277efk69hz2s452XNOuo/rMYLlnE62nXOy+5xcedSvT3augXROWY+Rcwqcc9LH0X30uPQ6GM4pGF8nJ52TK4+u3yWd+Dp5Nqb2dN5bM2Tvkdw18S1ssSUjZOz/dXV/r8fuq8eL53bPa20N4rJo0SIz9U2fP/3Q7bJp0yb313ofLeI88sgjJz0uHaHkizb91ibIpzpGF3199GdpE+U2bdp43a7TlIYMGWIKDG+88YYpBt13333ukT465W7w4MFmlW/9IK69c/VxKlasaKYQaTGkd+/eZn8tAmmz5vvvv9+0Tfn444+9XnudajRx4kQzlU9Hiri2a0GuX79+puCj+2g7Ff0Z2l9KH/tUr4drpIwOdNDvXdtdvaI87+vra9e1jrDRxai0h9Rll11mihx6ee+99+Scc87x+Ri+Hudk1/o42jNLR8/oZ2Ptt6UFLO1lpbdpXyTt+6TP+a+//moy5Cru5XTsntu1sKfT5bRw5cqlFsT0+XU9P/paa88svehsIy0m9unTxxRgPKdy5vS8axFo/Pjx5mfpc/XMM8+YQqUec9ZjzPR4PTy3aRFQC0d633vvvdeMetL8aN8wzcgll1wiueHZYN7zZ2vxTN9/XOfsos9JvXr1sp2Xr2N0vQdmfX/zfG88FQpKIu5hlp6FodxW17UxlwY6K10pToOo9I1CX1R9k9U3Hhf9H0sv+gbjWaXUIaP6BqZD1TyX3dTqo1Y19bE9/yHVvwxpRXbBggVex6BzTvW4ly1b5vWPn7656c9bs2aNe7urGl85bY972+t/x0ny0YPy4AVnmP/ptSmZS6Cck/bESkhI8KpIa7Vc/yrAOdl7Tq558PrXit27dwfFOQXj6+SUc9I86l9L9R9o/YtsMJxTML5OTjkn/VChedRj07+8BsM5BePr5JRz0g9nW7duNcerH1ac+DpprxUtrhw/ftycmx6PFh7095j4w0myx5KCUmZmhjkm5eqFpOfj+cFRRwzph209F/23z3W+uo/rnPQ11A/DOsJHn3cdvaFfq6SkJPdj6XOhozu0QbCr55L+8V5HVehnLl1Fu3Llyqa4os+Z6/OW7qs/yzV6Sff1LERqXvSiP8szS1988YV5/X/66Sf3ebrOSae2jRkzxowm0Q/3WlDSEVW6Tc9Viw89evQwn+v085uu+q2zU/TxdEW1r776ymRdM6Dvu0rPQwtQWiTRkSv6OGrSpElmJJJmSc/HdSz6czUzWkDTY9dRKrrCuI5m0l5Ivs7J83VyNa/Wn6v7eL5O/73GJwobnufvWqnc9TprYaNLly7m9xlt7n3RRRfJkiVLZMaMGV730+fc9dlYH9f1OHqt5+U6X9dnZNfrpI9x++23m+bhOopIR5ppgU9XT9fb9P9L/f9b/79R+v+ijphyvd6e5+T6Gcrz2LRApO8dOgXwlltuMdu0+PPEE0+499WeUlpE0oKQ5undd981edVCnj7fSjOp2XOdk4s+t3o8+v6hxS8two0ePVrOP/98U6DSn+l6nZKSksx5u14nPXbX86ZZ0v218KXPu2blzDPPNE3G9Rg9z8m1v75Onu8z+nq6tuvFdR89J9fPcT3vuTkn1+uk13q7/k6ho6qyvu/p+2RuFcssivbjltPqng7102qhVkmz0idZ/yHRub65GaGkbzRagSxVqlRA/cVKt82dN0+GjD0xVNDl3SFt5exmlfgrHOdUZOekt+tfv/QXR9fxB/o5nWw752T3ObnyqL/86S98wXBOWY+Rcwqcc9JfEjWP2vdRf4ENhnMKxtfJKeekvwO78ugaMee010k/MGtRTafuZJ3CFegjlLTIoB++Xc+TTvvS/kT6oVhH/WiRRIsxWhS6++67TcFGCwmuUVsne2xdnU0LMToyJjfHcrLt+mFaCyQ64uaVV17xGtGRdX+9djUE10bGWlDRD+w64kinUvmihSOdUuU5Akun+WkhxPUYOi1Li486VU6LGFmPUYso+v9KVroinRZbTnWuWsjT30N++eUX85nVtV1fA83fhx9+aIp0Sl8bFy2y6DRAXUFPc6wNm/UPtjrySq+16KLnrUUw1z56rQU2Fz1PHUChj+86Rtf5atFNs+957JoTnfKledDPz0eOHDFFOn1c1znpc+m6v6sxetbnwPNnZG2e/txzz5lz0WmOWnjWTOrIMf38rd9nXWjLRfPmORUxtxnT/8+1oKT/T+ix66gqz+ez2L/7u54r/Vqv9Ryynoc+X/q8Z52emBN9bN1XC3+aAxctMmoNQxtz6zQ3Fx1xpsU2veR0TloI0/PQ49FCb9b3Nz1fHfmkRSZXTSMnjFD6d+igvvj61xFXZdfzfwgdrpZTKLVyrJes9B+8rEtmuv5Bysr1j2Zut2d93PxsdzXQ82SGz4eEyINnN5TnJ65zb7/160Uy8oLmcmXHmtneoG0/p5MdY163c05Fe06urAXTOeV3O+fk/3NyTeUIpnPKzXbOyb5zcn2IdX14D4ZzCsbXyUnn5Mqj588J9HPy5WTnpMfkungad3s3sVnW48263fN2XTr9rrvuMh/cdcqU3qbFCi2i6egLLXZrf6DcPrbra18/Ky/HqHRqnY620GlsWV8HHbmifWy0YKKjY/Q2HYmkhQX9gK5Nrl2f/zzvpyM2dKSI52fArMeust5Xn4OczkkLEllXCNMP87l5DnSUtKsQ47n/3Llz3VNOfR2na3Se531y8xq4vtbH1tkCWffJ6VqLW61btzY9pLSwpgVHLcZNmzbN5+P7Op5T7aN05Js+thar9DXWJuyuwodrXx39paOjPOnIMV8Fx6y0GKQj0rRgqHRKnhYhtTCoq8PrKKOsx5aenu71XJ3sPHydU2543kdrGDr6zjMTSnOt+fX1+Fl/fk6/R/h6b8wJTbn/dcEFF5ghsTrX05OrAZnOuXSKm7rVkccGNfHa9ujPK+SZ304MTQQAAADgDFo0Wbp0qfkQ/7///c+M1vVcVU37Et10001+OTYdlfLSSy+ZopGv5ed1mx67fsj2HNGkIzR0QIHSooOO4vGk56MFC6Uj5nVEkueq3zoyRT+Q53ZZe+115Cq2uC46Mim3jbm1WKKjmXSEkouOENQRQDpySbmmwXmepxZz8kILC56PoZ+NXdPdckP319EtOrVMR3ZpAVKLG1m5RvNlHbWYWzpVTqe96fRLnTqo2XTR4psO+NBik+u51ulrOv3Mcxrtyehzqb21PKel6bRa5crN6T5XBUFXLNTz93wedRSVKxNFgYLSv3Sup1aIhw0bZv7ndjX30gq2/g+c26ZZgUz/p9A3Rb2+sVtdubtPQ6/bP5m5SSas2OW344NzeGYR8DfyCJuQR9iEPAY314djHa2gU4z0A7mv11o/R+nUm7w28y0Izz77rPnwryODtC+PzjhxXbSgoNu1oKBNsrVnkhY6dOSMHq+OTlJajNLpWDptSKdpaSFJC0yuqVFarGjYsKEZgODqe6RT/HQKmGu1slPRaXbLly83j6k/Q3sp6Ygqz5XmTkVfA/2cqsUuPQ89Li1ouIp5OppKG4rr1Cpt6XL11Vfn+fnUx9ABFfraa58p7Tfl6gucG9qMW++rzcr1WK666ir5/vvvsxWOtH+W9kJ6/fXXZfbs2fL555+bkT95oeevP2flypVeDcW1h5AWOnUqnz7POjrq+uuvNwUfnXqWG3rcWkjV6Yw6rU4Lqf/3f/9nCjg6vTI3z1WxfIxAyisdJahFVc2y9u/S/k46skr/nywqFJT+peHSQGhFVRvLaRh0fqpWr3VOqobeCTybd93Ru362kUpfzN7ih6OCE+XUCB/wB/IIm5BH2IQ8Bi9XEcBzSt/JLtqXx3PlKF+02KEjhrQIkNNUx7zQIo32ktHPb9pAWy86okgvCxcuND9Dp0Rp4VNXG9MihKtPkE4ZUoMGDTLNvHXUkU6d0uKBTvHT4oGrQKG3aZNp7dOkhQMtDOW0Qp0v2pBbR7zoSCl9XG3yrNOq7rnnnlw/hvY10oKWjkrSAoq2ZdEigquopYUlXelMC2g6ekd7m+lgibzQc9LCnBbctICizc61SJRb+vzq/R577DFTgNP3B21GrUUOz6bPSgtNOppGz0uLenl9L9HCoJ7/wIEDs63WrlMLtUCoPab69+9vnisdzZS1F1NOdBSSvuY67VGLSjrdU1fj0x5ZBfVcFQTNpB6nLjCgfcl0aqdmWUezFRWacmexYcMGsySgVkg1SA8++KCZA5pb2pRb5+fmpoGVjf9oaDVf33A93+C37T8u3V440UStRGSYzHu0t8RE0H4LRZ9FwB/II2xCHmET8vhfc1tfTbkDnU6X0mKLZzPqk9FRGldccYX5EJ7Tc6FFBp22pSOddMSQLsOek6yNgnPq4eW5QrAOCiiKkSHAyWRansdTvW/lpabhzHf+k9A5l3mpNjtBjXIxcmGbavLT4h1yNDlNPp25WYb3qu/vwwIAAABQSHTEkWslqNzQ/Tx72eQ0bUtHjmjfIl89jzzpiBAdcZETnYKnI0cA+A8FJeTK8LPqy89Ldoj+kWD8sl0UlAAAAIAgplO9cltMyi1tjqyX3NDlz7UdSU6qVatWgEcGID8oKMFLTk0V68WWkCaVS8mqXYfNZcS4lXI0KU2Gdq4tzauVLvLjRPCjwSdsQh5hE/IIm5BHFObMkbywcWoRnKuYQ/JID6UCFsg9lE5l5PhV8uH07HOonxncTK7uVLB/vQAAAABsF8w9lAAEp6QC7KHEKm9w09qirpKQU43xqjNrSXho9krr47+ulD6v5Dy/GSjoLAJFiTzCJuQRNiGPsIVmUJvEk0XYINNBeaSgBK+VFNasWWOufalVvrh8eE17ua1nPbm0fXWv2zbEH5XRf6wpoiOF07MIFCXyCJuQR9iEPP7HCR8cA2HUBWCLJIvzWJDvVxSUkCc9G1WUB/o3lhcubiUbRg7wuu29qXHy+/Jdfjs2AAAAoCiFh4eb6+PHj/v7UAAgV44dO2Z6PLnev04HTbmRb2GhIbLsqX7SedTfcjQ5zWy77etF8u6QtjKgRRV/Hx4AAABQ6E3Jy5QpI/Hx8eb7mJgYxzTjtW3ERXJysnk9eP7hb5kW5tE1DU/7I+lF37cKYlEFCkpw07Dr8qB5CX2pqHBZ+Hgf00Np2/5Es+2+H5dK94axkpSaLuVLRJpth46nyrIdB6VRpZKSnJYh1cvm7efAWfKTRaCwkEfYhDzCJuTxhMqVK5trV1EJ/vmwnJqaakZcOD2P8L9Mi/OoRaQqVaqYptsFgVXeClgwr/J2MrsPJckl789yF5VcSkaGyZF/Ry95GtSyirx9ZdsiPEIAAACg8GgvKf0QCQA2CgsLy9WoqbzUNBihBLeMjAxJSEiQChUqSEhI3tprVS4dJW9c3kYueGeW13ZfxSQ1ftkuGd7zsDSt6pyiG4omi0BBI4+wCXmETcijN/2gVhBTSJB3ZBE2yXBQHoP77JDn4G/cuNFc50ebmmXlqXOb5nr/gW9Ml8VbD+TrZyG4nW4WgYJEHmET8gibkEfYgizCJhkOyiMFJRSoa7vUkRHnNZPWNcrIJe2qS3T4f3+l0b5JQ86o6bW/jmhKSQv+/9EAAAAAAAgmTHlDgRvauba5qJEXtJDElHSJiQyV0GLFJCMzU76eu9Vr/5cnr5WHBzTx09ECAAAAAIC8YoQS3LQ5lzbfKshO9BFhIVI6JlzCQ0MkJKSYhIWGyObRg+SxQf8VkN6fulFmrE8osJ+JwFcYWQTyizzCJuQRNiGPsAVZhE2KOSiPrPJWwJy6ylteaez6vDJV4vYec2+7qG11efnSVn49LgAAAAAAnOpwHmoajFCCmzYN2759e5E0D9Nq7TtD2nltG7Nou2xO+K/ABOcqyiwCp0IeYRPyCJuQR9iCLMImGQ7KIwUl+C34jSqXlDG3dvLa9v2CbUXys2E3J70Jw37kETYhj7AJeYQtyCJskuGgPFJQgl+1q1VOnh7czP39xzM2yc6DiX49JgAAAAAAcHIUlOB313SqLZe0q26+TknLkM6j/5ZXJq/z92EBAAAAAIAcUFCCW0hIiMTGxprronb/2Y28vn/jr/WyaOuBIj8O2MGfWQSyIo+wCXmETcgjbEEWYZMQB+WRVd4KGKu85d+D/1uWrYfS9Ad6SY1yMebrp8aulClr4+XNK9pIy+pl/HSUAAAAAAAEJ1Z5Q75o07C4uDi/NQ8beUFzefb85l7bRv+xxly/NzVOPpu1WbbsO+7ehuDl7ywCnsgjbEIeYRPyCFuQRdgkw0F5pKAENw383r17/Rb8sNAQuerMWnJj1zrubeOX75Imj0/wKiLNitsnO2jcHdT8nUXAE3mETcgjbEIeYQuyCJtkOCiPFJRgnfv7e/dTSkxNz7ZPl9F/yyczNlFYAgAAAADADygowTqRYaFyS/e6p9zv6d9WyfCvFxXJMQEAAAAAgP9QUIKbdqGvXr26Fd3oL+9YU+rGFpd6scXN9xGhIfLqZa2kUaWSXvst2XZQknyMYEJgsymLAHmETcgjbEIeYQuyCJuEOCiPrPJWwFjlrXCkpWeYHkspaRnyzj8b5LU/17tvq1EuWq7sWEs61iknraqXNvsBAAAAAIC8YZU35Et6erqsXr3aXNvGVSSKCAuRu/o0lC9v6Oi+bdv+RHl+whq56N1Z5pKaHvzNz4KdzVmE85BH2IQ8wibkEbYgi7BJuoPySEEJbjpYTauQgTBorVuDWLm8Q41s25duPyRnPveXHEpM9ctxwXlZRPAjj7AJeYRNyCNsQRZhk0wH5ZGCEgLWiMHNJDIse4T3HUuR0X+s9ssxAQAAAADgBBSUENCrwa19doBsHj1INo0aKH2aVHTf9v38bRJ/OMmvxwcAAAAAQLCioAQ37UJft27dgOxGX6xYMXn/6vZybquq5vuMTJGOz/0lX8ze7IihhsEmkLOI4EMeYRPyCJuQR9iCLMImIQ7KI6u8FTBWefOv9XuOSN9Xp3ltu61nPXmgf2O/HRMAAAAAAIGAVd6QL9qFfunSpQHdjb5BpZJyT9+GXtve+SdOaj803lwmrNjlt2ODs7KI4EEeYRPyCJuQR9iCLMIm6Q7KIwUluOlgtcTExICfIqYjkvTiy7CvFsn9Py6V1PSMIj8uOC+LCA7kETYhj7AJeYQtyCJskumgPFJQQtAJCw0xU9ym3t/T5+0/LtwuDR79Qwa/PVMe/mmZHElKlbkb90n/16bJwz8tlzSKTQAAAAAAnFTYyW8GAlet8sXN6m+P/bJCvp67NdvtS7cdNJe4vcckOTVd1uw+Yi79mlaSXo3/WzEOAAAAAAB4oyl3AQvkptwaBT1uPX5dNS3Y6Mij4d8skokr95x0v4vbVZeXLmmVbfux5DQJDSkmUeGhhXiUcEIWEVjII2xCHmET8ghbkEXYJDPA85iXmgYFpQIWyAUlp1i45YBsiD8iMzbsk3FLd/rcRxt7N65cUvo2rWTeBDbuPSrnvjlDQooVk5cvbSX9mlUu8uMGAAAAAKAwscob8iUtLU3mz59vroNZu1pl5bIONeWFi1rKiPOayeDWVSVr4fiVyevk5i8XSrtn/5Q/lu+Ss16eKsdS0uVIcprZPjaHQhQKhlOyiMBAHmET8gibkEfYgizCJmkOyiMFJXhxwtKGLtERoTK0c215/fI2MuPBs+SJc5pm22f/sRS59etF2bbf8e1iOZSYWkRH6kxOyiLsRx5hE/IIm5BH2IIswibpDskjBSVARKqViZbru9aR28+qLyG5nOb6woQ1hX1YAAAAAABYiYIS4OHefo1k7bMDZPoDvU6575hF22XnwcQiOS4AAAAAAGxCU+4CFshNuTUKiYmJEh0dHZDd6Ata/JEk6f3SVNM3yeXVy1rJ9HUJ8tPiHe5+TN/ffKaEhVKbLUhkETYhj7AJeYRNyCNsQRZhk8wAzyNNuZFvERER/j4Ea1QsGSXvXNVWqpeNlkvaVZeNzw2UC9pUl4cGNJbS0eHuFeO+m7/N34calMgibEIeYRPyCJuQR9iCLMImEQ7JIwUleDUOW7BggWMaiOVGtwaxpmH3i5e0kpB/mytVLBUl713Vzr3PY7+skB/mbzOVaBQMsgibkEfYhDzCJuQRtiCLsEm6g/JIQQnIh071ykvHOuXc3z8wZpl0GPmnHPOYHgcAAAAAQLCioATk0129G3h9n3A0RYZ+Ms9vxwMAAAAAQFGhoATkU+f6FWTkBc29ti3YckDW7Tnit2MCAAAAAKAosMpbAQv0Vd50nmdoaGhAdqP3l9T0DOnxwhTZeSjJfN+zUax8dl1Hfx9WQCOLsAl5hE3II2xCHmELsgibZAZ4HlnlDfmWkpLi70MIOOGhIfL3fT2lauko8/0/a/fKwi37/X1YAY8swibkETYhj7AJeYQtyCJskuKQPFJQgptWUZctW+aIbvQFLSo8VK7uVNv9/W1fL5It+4759ZgCGVmETcgjbEIeYRPyCFuQRdgk3UF5pKAEFJChnWtJvdji5us9h5Olx4v/SP1HfpdXJq+TbfuP+/vwAAAAAAAoMBSUgAISExEm39x0pte2tIxMeeOv9dL9xSny56o9fjs2AAAAAAAKEgUleNHGYci/SqWipGX10tm2a+v74d8sku0HGKmUW2QRNiGPsAl5hE3II2xBFmGTUIfkkVXeClggr/KGgrF612G5+uO5knA0eyO2ZwY38+q1BAAAAACALVjlDfmitcWDBw+aa+RfkyqlZMFjfWXjcwPl73t7yL19G7pve/zXlfRTygWyCJuQR9iEPMIm5BG2IIuwSaaD8khBCW7ahX7NmjWO6EZfFEJCiknd2BJyW6/6Elsy0r1d+yn1f22aPPf7almweb9fj9FWZBE2IY+wCXmETcgjbEEWYZN0B+WRghJQyEJDikn3BrHu77VQvWb3Eflg2ka5+L3Z8vgvK/x6fAAAAAAA5BUFJaAIPHleU3l6cDO5tnP2/klfztkiU9ft9ctxAQAAAACQH2H5uheCUrFixSQ6Otpco2CVigqXa/5txl2/Ygl5LMuopJ8WbZceDf8bxeR0ZBE2IY+wCXmETcgjbEEWYZNiDsojq7wVMFZ5Q27o/3aHk9Kk1YhJ7m0RoSEy46FeUrFklF+PDQAAAADgTIdZ5Q35kZGRIfHx8eYahUur1aWjw+WCNtXc21LSM+Saj+fJocRUcTqyCJuQR9iEPMIm5BG2IIuwSYaD8khBCW4a+I0bNzoi+La4p29DqV422v29Nut+b2qcOB1ZhE3II2xCHmET8ghbkEXYJMNBeaSgBPhRjXIxMuPBs+T7m890b/th/jZJSw/+Nx8AAAAAQOCioARY4Iy65aVbgwrm633HUuTeH5f6+5AAAAAAAMgRBSV49/UpXdoR3ehtdFvP+hIacuK5/3XJTlm187A4FVmETcgjbEIeYRPyCFuQRdikmIPyyCpvBYxV3nA63vxrvbw8eZ35+t6+DeX8NtXkl8U7pH/zytKgUkl/Hx4AAAAAIIgdZpU35Ic2Ddu+fbsjmofZanDr/1Z908JStxemmOu+r06T1/5cJ+OX7ZIN8Ucl2JFF2IQ8wibkETYhj7AFWYRNMhyURwpKcGTwbVWjXLRUKBHp87bX/lwvw79ZJH1emSo/L94uwYwswibkETYhj7AJeYQtyCJskuGgPFJQAiyi82zPahx7yv3u/n6pNHj0d9l+4HiRHBcAAAAAAJ4oKAGWeXpwcxlxXjPp1ejkhaXU9Ezp+vwUue/HpXLoeGqRHR8AAAAAAGH+PgDYIyQkRGJjY801/CcqPFSGdq5tLglHkyUxJV1qlIsxtx04liJtnpnstf//Fm6XXYcS5fPrOkpYaHC8dmQRNiGPsAl5hE3II2xBFmGTEAflkVXeChirvKGwpaVnyHtT4+SlSSdWg/O08LE+Uj6HHkwAAAAAAJwMq7z9a/369XLxxRdLxYoVJTw8XCpUqCC33HKLeWKySk5OlpEjR0rDhg0lOjpa2rZtK5Mne48ECXbaNCwuLs4RzcMCmY5C+r+zGsjm0YNkUMsqXrc98etKGbd0pyzcckACuVZMFmET8gibkEfYhDzCFmQRNslwUB6DtqC0evVq6dChg4wZM0ZKliwpffr0Mds/+OAD6d+/v6Snp7v31a+18PTYY49JWFiYDB8+XCIiImTAgAEyZcoUcQoN/N69ex0R/GAx6sIWXt+PX75Lbv92sVz07iz5a3W8BCqyCJuQR9iEPMIm5BG2IIuwSYaD8hi0BaVhw4bJ0aNH5cMPP5QNGzbIH3/8Ya6bN28uc+bMkXHjxrn31SLTb7/9Jt26dZPFixfLSy+9JDNnzpROnTrJddddJ6mpNDyGnUpFhcuqp8+WamWis9124xcLZNHWA345LgAAAABAcAsJ1tFJs2bNknvuuUduvPFGsxS7KlOmjNx2223m6/nz57v3f+utt8z1m2++KZGRJ/rPhIaGyuOPPy5btmyRv/76yy/nAeRGTESYTLirm8+i0rv/xPnlmAAAAAAAwS0oV3lr0qSJHD9+3OcQs7S0NHfBSOlQtFWrVkn9+vWlVatWXvv27NnTTH3TXko6TS7YaRf66tWrO6IbfbApGRUu/9zfUyav2iPxh5PkqXGrzHb9PhCRRdiEPMIm5BE2IY+wBVmETUIclMegPUNtwu0abeTJNdWtS5cu5nrXrl3mWptwZ6XFpJo1a5qGWk7gpOAHo/DQEBnYoopc26WOtKpRxr39md9WycHjKbLjYKJkZARGo26yCJuQR9iEPMIm5BG2IIuwSYiD8hhQI5R++uknWbRo0Sn3u+GGG6ROnTrZts+ePduMNtIRTH379nUviacqVark87HKli0rO3bsECfQ5uTr1q0zK925RnAhMLWuXlqWbjtovv54xiZzMdtrlJEfbukkEWF2v7mRRdiEPMIm5BE2IY+wBVmETdIdlMeAKiiNHTtWPv/881Pupyu6ZS0oJSUlyU033WS+fv31193VQtcLHBMT4/OxdJTT/v37c/xZycnJ5uLiKlDp1DrX9Dr9WXrRKXie0/Bc2zVwnku857Rdj1X7Qbke13O78ly57mTbdSU7fVzP7fq4uu3gwYPm8V0/V7fr4+R07Lafk69jd8I5Xdqumnwzb6ukpnuPSFqy7aBMWbNb+jatbPU56e2aRd03mF8nzikwzsmVR70+2bkG0jllPUbOKXDOSY/H9W+17h8M5xSMr5NTzskzj/qzguGcgvF1csI56T6HDh3y+hwT6OcUjK+TU84p3eOzTCCeU15WpwuogtJnn31mLvmhDbpXrlxpmnK7RiepEiVKmGvPopCnlJQUc8nJqFGjZMSIEdm262pxxYsXN1/HxsZKvXr1ZNOmTaZnk4sOg9OLVi/1DdClbt26UrFiRVmxYoUkJia6tzdu3Ng0FtfH9gxUy5YtzfS8BQsWeB1D+/btzbEvW7bMvU0D1qFDB/Pz1qxZ494eHR0tzZo1M/vrKDBXI/PSpUubEV07d+6U7du3u/cPlHPSvlgJCQmyceNG93annNOz3UvJl6tSZMWe/45NfTttlTQpnS5hJSvI4pVrpWxIooT8+3rbck76hnbs2DHzdbC/TpyT/efkKrbrIg0NGjQIinMKxtfJKecUHx9v8qj/VteoUSMozikYXyennJOuoOzKo/7uGAznFIyvkxPOqVatWuZae+N6fq4L5HMKxtfJKeeU6VFICsRz0v1zq1imZykqSH355ZdyzTXXmBdpxowZXr2VDhw4IOXKlZPzzjtPfv3112z3rV27tgnIvHnzcj1CSX/B27dvn5QqVSqgKre6TVe/035SrvtSjQ78c9Lbtu47Jj1emiq+XHNmTXninCZWnZPerr+c6huo6zUJ9teJc7L3nFx5bNeunfkFIBjOKesxck6Bc06pqakmj/pvtfaLDIZzCsbXySnnpL8Du/Ko9w+GcwrG18kJ56T7aBbbtGnjPq5AP6dgfJ2cck7pHp9lsgqEczp69Khp/aNFJldNw7EFpblz55rV2vSJ0CqgFnt8FY30FzSt4rlG5rgadletWjXHYpMvWlDSymBunnzbaLi0ylmhQgUTLAQP/d/80vdny/zNB3ze/vn1HaVHw9xXogsbWYRNyCNsQh5hE/IIW5BF2CQjwPOYl5pG4J1dHqxdu1bOPfdc84JqQ29fxSR1wQUXmGFhP//8s9d21/Q67cnkBBp2HY0ViKHHyWmh9KNrOkjlUlE+bx/6yTxp+sQE2RB/VGxAFmET8gibkEfYhDzCFmQRNglxUB6DdoSSziXs0qWL7N6920x5u+qqq066b4sWLUzPIy0q6f3GjRsnQ4YMMR/EtTBVuXLloB+hpEPddO5n8+bNvYaKIrgcT0mTg8dT5UhSmvR/fZrk9A7Qs1GsfHB1e7+sCEcWYRPyCJuQR9iEPMIWZBE2SQ/wPOalphFQTbnzYtiwYaaYpE2ytIHVY4895nW7rgJ3ww03mK91Hx2NNHToUOnatatZ8e348eOmN8FXX32V62JSoNPaojYSC9IaI/4VExFmLuqZwc3lsV9W+Nzvn7V7Zeq6vdK3aaUiPkKyCLuQR9iEPMIm5BG2IIuwSaaD8hi0BaV//vnHPfpo5MiR2W7v0aOHu6CkLrnkEtPE7cUXXzSrA+hKAQ8++KAZuQQEq6vOrGUuczbuk8s/mJPt9pu+WCDntaoqV3SsKZ3qlffLMQIAAAAA7BO0BSVdci+v6tevL++//36hHA9gszPrlpfVT/eXzqP/kgPHU71uG7t0p7k0rlxSfhjWSeLij0rzaqUlPDT45wQDAAAAABzWQ8lfArmHkkZBj1uP33O1OzjH4q0HZNq6BHntr3U59lZyiQgNkZT0DCkVFSa3n9VAbuxWp8By45lFXZnuzu8WS9taZeX1y1pLGIUsFDHeG2ET8gibkEfYgizCJpkBnse81DQoKBWwQC4oAS6TV+0x093yokKJCLmlez25tH0N2bD3iFQsGSU1ysWc1nGkZ2RKv1enStzeY+b7j4e2l95Nir6nEwAAAAA4weE81DT4Uz/c0tLSZP78+eYazqaNuDePHmQub1zRRqLCT/1WkXA0RUb+vlpaPT1JLnp3tnR7YYpc/fFcs6pcXmkG58ybJ7M37HUXk1Tc3qN5fizgdPHeCJuQR9iEPMIWZBE2SXNQHoO2hxLyv8Qh4EmbcuslOS1dvp27VY4mp0lsyUj5as5WqVI6SupVLCG/L98lW/Ydz3bf6esTpOkTE+X5i1pI9bIx0qlueQkJOfmwz/gjSXLtJ/Nk9a4jkil7vW7bcSCxwM8PyA3eG2ET8gibkEfYgizCJukOySMFJQC5EhkWKtd2qeP+/rIONd1fP9i/sbw3NU5G/7HG530fHLPcXN9+Vn25t18jn/ukpGXI+OU75e7vl+Z4DJ/P3iJnN68sraqXkeKRvH0BAAAAgL8w5Q1Agbile12JCDvxlhL573VWb/69Qa76aK7M3JAgB455r8T45t/rT1pMcrnyw7nS7MmJ8tOi7bJ295ECOnoAAAAAQF7QlLuABXJTbo1CYmKiREdHB2Q3evhfYkq6/G/hNmlXq5yEhRaTfq9OO+n+jSuXlJcuaSXnvDkj3z/z8g415Nnzm7P6GwoN742wCXmETcgjbEEWYZPMAM8jq7z5UaAXlHSuZ2hoaEAGH3a68J2ZsmjrwTzdp3O98hIdHiJ/rTnRQ6lf00ry9pC28tH0TfL8hOzT6jrULiuvX95GqpaJLrDjBlx4b4RNyCNsQh5hC7IIm2QGeB5Z5Q35oqFfsGCBYxqIoWj8dFsXs1rctPt75Wr/Fy9uKV9c116urp8u3RqUl6qlo+TOPg0kPDREbu1ZT8bc2lnCQ73fmOdvPiBDPppr3ryBgsZ7I2xCHmET8ghbkEXYJN1BeaSrLYAiUbN8jKx5pr9ZDe7Z8avMCnBZPTaoiVzcrrp5840KKyafDm0vYWHeb1PtapWV9SMHyupdh+XlSevkz9V7zPZNCcdkytp4OatxpSI7JwAAAABwKkYoASgyUeGh0qhySfnyhjNkw8gB0rF2Ofdt+v2N3ermelhokyql5MNr2sl9/Rq6t13/2QIZ8tEcSUoN/r8GAAAAAIA/UVAC4BfaRPv7W86Uf+7rKXHPDcxXU20tPt3Ws75p7u0yc8M+ueu7JZJwNFnS0jMK+KgBAAAAAIqm3AWMptxA0Wdx677j0u+1qZKU6l1A0kLTL8O7mJFRQH7x3gibkEfYhDzCFmQRNskM8DzSlBv5lpKS4u9DAPKcRe3PtPrp/nL/2Y28tq/ZfUS+nbe1EI4OTsN7I2xCHmET8ghbkEXYJMUheaSgBDetoi5btswR3egRfFnU6v+N3epI8Qjv0Ugjxq2ST2ZskoVb9hfCkcIJeG+ETcgjbEIeYQuyCJukOyiPFJQABI3IsFA5r3XVbNuf/m2VXPb+HJm5IUFS6asEAAAAAKeNghKAoPLEOc3khq51JDLM++0tLSNThnw0V859c4ZsiD/qt+MDAAAAgGBAQQletHEYEMhZjI4IlcfPaSprnx0gb1/ZVtrULJOtr9KwrxaaZnlAbvHeCJuQR9iEPMIWZBE2CXVIHlnlrYAF8ipvQDDSt7hbvlwok1bt8do+vFc9uaBNNalWJsYUoQAAAADA6Q7noaZBQamABXJBSaOgx63HH4jLGyJ4FHQW9fFS0zPl/alx8vLkdV63VS8bLX/c2U1KRoWf9s9BcOK9ETYhj7AJeYQtyCJskhngecxLTYMpb3DTLvRr1qxxRDd6OCuL+kYeERYi57TK3rB7+4FE+Wt1fIH8HAQn3hthE/IIm5BH2IIswibpDsojBSUAjlGnQnG5t2/DbNtnxSX45XgAAAAAIFBRUALgKLf3biCbRw+S+Y/2kejwE72Txi7dKZsTjvn70AAAAAAgYFBQgte0oOjo6ICc54ngUhRZjC0ZKZe2r26+TkrNkEvfny3r9xwptJ+HwMV7I2xCHmET8ghbkEXYpJiD8khT7gIWyE25Aac5lpwm57w5QzZ5jE46t1VVeePy1o74BwAAAAAAPNGUG/mSkZEh8fHx5hpwQhaLR4bJg/0be20bt3SnjPpjTaH+XAQW3hthE/IIm5BH2IIswiYZDsojBSW4aeA3btzoiODDbkWZxT5NKkqH2mW9tv26ZIdZ7jM3/ly1R7qM/lvOf3umHDiWUkhHCX/ivRE2IY+wCXmELcgibJLhoDxSUALgaGGhIfLVjWfIixe3dG/bczhZOoz8Uyau3J3j/ZLT0uW2rxfKjV8skB0HE2XJtoMy4PXpRXTUAAAAAOBfFJQAOF5kWKhc0r6GvHFFG/e2hKMpcsuXC80KcFltiD8io/9YI78v9y447T6cJB9MiyuSYwYAAAAAfwrz60+HVbQJsTbfohkxnJrFc1tWkfmb9suXc7a4t93x7WI5nJgqEWEhck7LKrJ1/3EZ9MYMSc/wPSXu81lb5LL2NaV0THgRHjkKE++NsAl5hE3II2xBFmGTYg7KI6u8FTBWeQOCY/W39s/+KYmp6bnav1/TSjJp1R739zd3rysPD2jsiH9EAAAAAAQPVnlDvmjTsO3btzuieRjs5u8s6upvoy5skat9b+leVz64pr1Mu7+XhIWcKCB9MG2j9H11milMIfD5O4+AJ/IIm5BH2IIswiYZDsojBSU4Mviwmw1ZPLdVVbmjdwOpXjba5+0/Duskf97TXR4a0Nh8X7N8jJzdvLL79g3xR+XvNfFFdrwI7jwCLuQRNiGPsAVZhE0yHJRHeigBgA+hIcXknr4NzSUpNV1W7jws70zZIKWiw+XO3g2kdoXi2e7z5LlNZfyyXe7v1+4+Iue2KuIDBwAAAIAiQEEJAE4hKjxU2tUqKx9f2+Gk+1UsGSXTH+gl3V6YYr6fv3m/7DyYKFXLnBjltHXfcQkPKyZVSvse9QQAAAAAgYKCEtxCQkIkNjbWXAP+FMhZrFYmWopHhMqxlHSZu2m/dB79t9zUrY60rlFW7vxusaRlZMrIC5rLlR1r0rQ7QARyHhF8yCNsQh5hC7IIm4Q4KI+s8lbAWOUNwM1fLPBa9c2Xwa2ryuuXtymyYwIAAACAU2GVN+SLNg2Li4tzRPMw2C3Qs/js+c2lbEz4Sff5dclOiT+SVGTHBOfmEcGFPMIm5BG2IIuwSYaD8khBCW4a+L179zoi+LBboGexYqkoWfxEP/nu5jNPut/wrxdJegaDRG0X6HlEcCGPsAl5hC3IImyS4aA80kMJAArJmXXLyw+3dJJnflslEWEhckGbalIyKkzu/G6JuX3+5gNS75HfzdcdapeVly5pJbXKZ189DgAAAABsQ0EJAApRxzrlZNztXd3fp6ZnyIsT18r2A4le+2lx6b4fl8qPwzr74SgBAAAAIG+Y8gY37UJfvXp1R3Sjh92COYvhoSEy4a7uPm/TotKOg96FJvhfMOcRgYc8wibkEbYgi7BJiIPyyCpvBYxV3gDkxtyN++SyD+Zk2z7kjJpyUbvqUrdCcSkTE+GXYwMAAADgTIdZ5Q35kZ6eLqtXrzbXgD85IYtn1C0vvwzvYi5f3tDRvf3ruVvlwndmSeunJ8uTv66gabcFnJBHBA7yCJuQR9iCLMIm6Q7KIwUluOlgNa1CMmgN/uaULLauUcZcOterYEYmhYYU87r989lbZPDbMygq+ZlT8ojAQB5hE/IIW5BF2CTTQXmkoAQAfqaFpJEXtJB/7uspQzvV8rptxY7Dcv1n8x3xDxIAAACAwEFBCQAsUaNcjIwY3Fw2jx4kLaqVdm+fum6vnP3aNBm3dKe0f/ZP6TjyT1mx45C57cCxFHMBAAAAgKJEU+4CFshNuTMyMiQhIUEqVKjgiI70sBdZFElNz5Dnfl8tn87cnOM+XeqXl/mbDpivf7+zq9SvWLIIj9A5yCNsQh5hE/IIW5BF2CQjwPOYl5oGBaUCFsgFJQD2+WzmJnlq3KpT7texTjn54ZZORXJMAAAAAIITq7whX7QL/dKlSx3RjR52I4v/ubZLHTm3VdVT7jdv035Zv+dIkRyT05BH2IQ8wibkEbYgi7BJuoPySEEJbjpYLTExkea/8Duy6O3NK9rIvEd6y6gLW8i0+3vJumcH+Nzv+/nbivzYnIA8wibkETYhj7AFWYRNMh2UxzB/HwAA4NQqloqSKzrWdH8//9E+MmfjPgkPDZFhXy00276Zt1WuPKOm1I0t4ccjBQAAAOAEFJQAIADFlow0U+H0Lx/R4aGSmJoux1PS5ayXp5rbh/eqJ9d3qSPlS0T6+1ABAAAABCGmvMEtNDRUGjdubK4BfyKLuVesWDFpWCn7iKS3p8RJu2f/lEOJqX45rmBCHmET8gibkEfYgizCJqEOyiMFJXh9MC1Tpoy5BvyJLObNPf0a5XjblR/OkYyM4J+/XZjII2xCHmET8ghbkEXYpJiD8khBCW5paWkyf/58cw34E1nMmx4NY2Xpk/3kmcHN5Ooza3ndtnLnYan7yO9y/tsz5elxqyThaLLfjjNQkUfYhDzCJuQRtiCLsEmag/JIDyV4ccLShggMZDFvSkeHy9WdapuvHx3URJo8MUE8F5ZYsu2guWhB6Y0r2vjvQAMUeYRNyCNsQh5hC7IIm6Q7JI+MUAKAIBMVHiobnxson17XQSqW9G7KPXbpTvl+/la/HRsAAACA4EBBCQCCkM7Z7tWoonx385lyXquqXrc9OGa5NHl8gkxetcesEgcAAAAAeVUsk08TBerw4cNSunRpOXTokJQqVUoCiUYhMTFRoqOjHdFADPYiiwXveEqa6aO0bs9Rr+1d61eQz6/vKKEhPM85IY+wCXmETcgjbEEWYZPMAM9jXmoajFCCl4iICH8fAmCQxYIVExEmv9/RTaqXjfbaPmNDgvy2bKffjitQkEfYhDzCJuQRtiCLsEmEQ/JIQQlejcMWLFjgmAZisBdZLBxhoSHy5z095LFBTby2T1kTL4cSU+XNv9bLgs37/XZ8tiKPsAl5hE3II2xBFmGTdAflkVXeAMBhDbtv7FZXrulUW5o9OUFS0zPllyU7zcWYLFI8IlSev7ilDGpRJSCH6QIAAAAofIxQAgAHiggLkY51yvm87VhKuvzfN4vlvakbi/y4AAAAAAQGCkoA4FAdavsuKLlMXRdfZMcCAAAAILCwylsBC/RV3nSeZ2hoKNNc4FdksWjEH0mSe75fKhmZmdK7SSV5bfI6OZKc5rXPumcHmNFMTkYeYRPyCJuQR9iCLMImmQGeR1Z5Q76lpKT4+xAAgywWvoolo+SrG8+Qb246U27oWkd+vLWTRIR6/7PQ8LE/TMNupyOPsAl5hE3II2xBFmGTFIfkkYIS3LSKumzZMkd0o4fdyKJ/NK5cSuY/2kfu7N3Aa/s7/2wQJyOPsAl5hE3II2xBFmGTdAflkYISAMCtdEy43NG7gbSuUca97dOZm2XVzsN+PS4AAAAAdqGgBADwEhpSTH4Z3kUubFPNfJ+SliED35gu3V74W6av32t6LyWnBf9fXAAAAADkLOwkt8GBtHEYYAOy6H/PXdhClm4/KHF7j5nvt+1PlKs/nue+vVPd8nJbr3qyYPMBqVU+RppXKy3JqRlSuXSUlC8eISEhgdeEMCfkETYhj7AJeYQtyCJsEuqQPLLKWwEL5FXeACCrRVsPyIXvzMrXfWuWizHFpQ+ubidlYiIK/NgAAAAAFCxWeUO+aG3x4MGD5hrwJ7Joj7Y1y8rU+3vK7WfVz/N9t+4/LvM27ZfWT0+WJdsOSqAij7AJeYRNyCNsQRZhk0wH5ZGCEty0C/2aNWsc0Y0ediOLdqlVvrjc26+RrH66v8x7pLdZCa5q6ag8Pcb5b8+U5dsPeW1LTEmXN/9aLx9N32j1P7jkETYhj7AJeYQtyCJsku6gPDqqh9LevXulefPmMmDAAPnss8+8bktOTpaXXnpJPv/8c9m2bZs0adJEnn/+eenbt6/fjhcAbBIdEWouatbDvWXt7iOyYMt+6d4gVsqXiJCfFu0w276cs8Xn/c99a4a8dllr6VCnnLw/NU6+mP3ffvUrlpCejSoW2bkAAAAAOD2OKijdeuutEh8fn227Vg4vvvhi+e2330whafjw4TJjxgxTeJo8ebL06tXLL8cLADZrVLmkubhcdWYtcz20cy35YNpGmb1xn2nk7emu75f4fKxrP50v4+/oKs2qli7kowYAAABQEBxTUPr2229lzJgxPm/74IMPTDGpW7dupoAUGRlpikw9e/aU6667TtavXy/h4eES7IoVKybR0dHmGvAnshjY6lcsKS9c3Mr9/Yb4o9LnlamnvN/wrxfJP/fbV8Anj7AJeYRNyCNsQRZhk2IOyqMjVnnbvXu3NGvWTEqWLClbtmyRoUOHek1509tWrVolS5YskVat/vsQNGnSJDn77LPljz/+kP79++fqZ7HKGwBkN3bpTrnj28Wn3O/LGzpK/OFkObNeealWJrpIjg0AAADACazylsVNN91kuqxrfyRffZW0mFS/fn2vYpLSEUoRERFm1JITZGRkmCmBeg34E1kMPue1qiobRg6QazvXNt/f3L2urHt2gNzdp6HXfld/PE/u/XGpdBn9txxNThMbkEfYhDzCJuQRtiCLsEmGg/IY9AWlTz/91Exnu/vuu6VHjx7Zbt+1a5e5btu2bbbbtJhUs2ZNiYuLEyfQwG/cuNERwYfdyGJwCgsNkafOayabRw+SRwY2kYiwELmzTwP59NoOPvfvOPJPK4pK5BE2IY+wCXmELcgibJLhoDwGVA+ln376SRYtWnTK/W644QapU6eOWa1NC0m6stvIkSNzHM6lKlWq5PP2smXLyo4dO3L8Wbo6nF6yPl5aWpq5qJCQEHPRQHmGyrVd+zV5zjzMaXtoaKiZh+l6XM/tKuuyhDltDwsLM4/rud01v9PXdn2cnI7d9nPydeyck/3n5Pnzg+WcTrbd6efUomoJ8eV4SrqM/n21PHtBC7+ek+tYXfs49XXinOw4J9dx6nWwnFMwvk5OOyfXzwimczrVds7JrnPy/B0y6zEG6jkF4+vklHNK9/g6EM8pL4WwgCoojR071ue0taz69OljCkpaWEpMTJSvvvrKNNr2xfXCxcTE+Lxd77d///4cf9aoUaNkxIgR2bYvXrxYihcvbr6OjY2VevXqyaZNm8wUO5fq1auby7p168z8RJe6detKxYoVZcWKFeb4XRo3bixlypQxj+0ZqJYtW5rRVAsWLPA6hvbt20tKSoosW7bM63w7dOhgft6aNWvc27VpmPaS0v21aOcqMOncSV35bufOnbJ9+3b3/oFyTjqNMSEhwVSIXTgn+89J39COHTtmvg6WcwrG16kgz6l3w7Ly17oDktWEFbvk6cHN/XpOmkedNq09+Bo0aODo14lz8v856RB6zaP+W12jRo2gOKdgfJ2cck4bNmxw51F/dwyGcwrG18kJ51Sr1omVZrWViecf+wP5nILxdXLKOWVmZroLSYF4Trq/OL0p93vvvSe33nqrjB49Wh588EH3dv3HzrMp9/Lly82Letddd8mrr76a7XHOOOMMU1DSld5yO0JJf8Hbt2+fu4FVoFRu1dq1a00/Kf35ru1Uozmnoj4nvdb/5/QfF709GM7pZNs5J/NIsmT7IcnMzJCGFUvIHd8vlanrEswtvRtXlHeubC2hIcX8ck6uPDZs2NCs+Onk14lz8v856fFoHrW4qY8dDOcUjK+TU85JP/y48ujaFujnFIyvkxPOSb/WAqd+aHZ9jgn0cwrG18kp55SRkWHy2KhRoyy/7wbGOR09etTM1MpNU+6gLChplU4rdq1bt5apU6d6valkLSgdOHBAypUrJ+edd578+uuv2R6rdu3apuI4b968XP1sVnkDgNP31Zwt8tgvK9zfP3N+c7n6zBN/fQQAAABQOPJS0wioKW+5pSOStKqmQx+feOKJbLfrsLPHHnvMNOK+8MILzX465Exra66ROq6G3TrFIevqb8FKq5U6PK5q1apeRTigqJFFDGxRxaug9PgvKyThSLLcflZ909y7KJFH2IQ8wibkEbYgi7BJhoPyGJQFJde8wK+//trn7TovUS86UkkLShdccIG89tpr8vPPP5vvXVyjmLQnk1OCr3MtK1euHPTBh93IIsoVj5ClT/aTViMmube9/td6WbT1gLx5RRspExNRZMdCHmET8gibkEfYgizCJhkOymNQnt0///xjRhv5uigtJOnXroLR7bffbppyDxs2TGbOnGm2jRs3zjTc1iFel1xyiV/PBwCcqHR0uLx2WWuvbdPXJ8jNXy702zEBAAAACOKCUl5pZ3YtLuk0ua5du5rV2bSnUlJSknz44YemsggAKHrnt6kmz13QwmvbvE37ZeXO/1aiAAAAAFD0KCj9S0ch6TS4m2++2fRWGjJkiCxcuFAuvfRScQodjqdLBAb7sDzYjyzC05Vn1JTNowfJHWfVd2+74oM5sudwUpH8fPIIm5BH2IQ8whZkETYJcVAeg3KVN39ilTcAKByJKenS7YUpknA02b1t4l3dpVHlkn49LgAAAMCJNY08lcyOHz+e6303b94s1113XV4eHhY0D4uLizPXgD+RRfgSHREqz57f3Gvb2a9Nc/fHKyzkETYhj7AJeYQtyCJskuGgPOa6oJScnCwlS5Y0haLc7j9mzJjTOTYUMQ28rpDnhODDbmQROTm7WSWpXCrKa9vUdSdW9iws5BE2IY+wCXmELcgibJLhoDyG5XbHyMhI81dgLSqpTp06SVRUlBQrVizH0UyhoaEFd6QAAMfTf3P+ub+nNH58gnvb0+NWSed6FSQiLPjnqQMAAAC2yPNv3+Hh4eZ6xYoVcvHFF8vUqVPloosukuXLl5vrf/75x1z3798/x2ITAAD5FRUeKuueHSBlY078e7Qx4Zj8szbe34cFAAAAOEqeC0quIlF0dLQMHz7cfK3XOnLJ8/urrrqqoI8VhUy70FevXt0R3ehhN7KIU9HRSI+f09T9/eJtBwvtZ5FH2IQ8wibkEbYgi7BJiIPymKspb3fffbfpnaTFpBEjRkjFihVPeR9GJwVu8AF/I4vIjS71K7i/fvefOGlVvbRMWrlHLmpXXTrXK19g/w6RR9iEPMIm5BG2IIuwSYiD8pirkpkuGXf06FHTQ+mPP/6QN998s/CPDEUuPT1dVq9eba4BfyKLyI1KpaKkWplo9/fDvlokPy3eIUM+miuNHp8g5701Q1bsOHTaP4c8wibkETYhj7AFWYRN0h2Ux1yNUHrqqafclbbZs2dLqVKlcjVKCYFFC4aHDh0q9CW4gVMhi8itu/s2lPt+XJpte0pahizbfkjOeXOG1K1QXFrXLCN392koNcrF5PlnkEfYhDzCJuQRtiCLsEmmg/KY61XelE4fcC19p09Qv379zJOk17t37zbXSq8TExML54gBAPjXxe2qy+5DifLqn+slPePEP9oNKpaQ9fFH3fto0269/LRoh7SvVVY+vKa9lC0e4cejBgAAABxUUEpLSzPFo5SUFHdfpcjISOnSpYv5Puv1/v37zcpvAAAUpv87q4Fc07m2rN55WGpXKG6mwu06lCiD35op8UeSvfZdsOWAtHlmsvRuXFFGDG4m1cvmfcQSAAAAAJFimbkYh6UNuXX+31dffSV33nmnlClT5pQPvHLlSunQoYMcP35cnOTw4cOm55SO4NKpgYFER58lJCRIhQoVHNGRHvYiiygIh5NS5eJ3Z8m6Pf+NVvIUHlpM/rizu9SvWOKkj0MeYRPyCJuQR9iCLMImGQGex7zUNHJ1diNHjpRmzZrJ+vXrZcmSJWaU0skuycnJUqJECXn99dcL6pxQBDTs2hsrEEOP4EIWURBKRYXLpLt7yObRg2Tx432lf7PKXrenpmfK2KU7T/k45BE2IY+wCXmELcgibBLioDzmaoTShg0b5IcffpDvv//eTGPLzVLM+rC6nxM6mwfLCCV9rVasWCHNmzeX0NBQfx8OHIwsojAkp6XLz4t2yPjlu2T6+gT39s+v7yglIsOkdY0yEhqS/d838gibkEfYhDzCFmQRNkkP8DzmpaaRqx5K9evXl0ceecRcxo8fL88884zMmzfPbH/11VelcmXvv/oq10glBA4tAmozdSd0o4fdyCIKQ2RYqFzesaZc1qGGtHxqkhxJTjPbh34yz73PM4ObydWdanvdjzzCJuQRNiGPsAVZhE0yHZTHPK3ypgYNGmQun3/+udx7770ybNgwM2opN32VAADwNx09e06rqvLtvK3Zbnty7EoZ0KKKVCgR6ZdjAwAAAAJFvif1DR06VJYuXSofffQRxSQAQEB54pymcsdZ9bNtz8gUeevvDdm2H0nJkHmb9suew0mSmOKsqdwAAABAvnsonapPkmuKW0REhDhdIPdQ0tdTj1uPPzd9soDCQhZRlI6npMmnMzfLixPXurfNfOgsqVYm2nx9LDlV2j3zpySlZXjdb/bDZ8mx5HSpF1ucnKLI8P4Im5BH2IIswiaZAZ7HAl/lzdOvv/4qnTp1Mg88efJk9/bevXtLTEyMdO3aVcaMGZO/I4dfadh1tFkghh7BhSyiKMVEhMk1nWp5bbv647mmibf6dt62bMUk1WnU39Lnlaly/WfzJSmVUUsoGrw/wibkEbYgi7BJMQflMU8jlN5++22566675JJLLpEOHTrI5ZdfLlWqVDG3abPu1atXy7Rp08zXH374oVx//fXiNIE8QiktLU0WL14sbdq0kbCwPLfXAgoMWYQ/xB9Oko7P/ZWv++oqcUeT06RSqUgJCwmRWuVjZHiv+tKlfoUCP044G++PsAl5hC3IImySFuB5LLQRSs8//7y89NJL8s0338jdd9/tLiYpbdR93333ydixY81qcLoSHAJziUPABmQRRa1iqSh5dGCTHG9vVb20TLirm8/btJik9hxOlh0HE2VW3D4Z8tFcRi6hUPD+CJuQR9iCLMIm6Q7JY54KSvv375cWLVqccr8uXbpIfHz86RwXAABF7oaudWTUhb7/nXtmcFNpXLmUbBg5QD65tr18fn1H+e32rtK5XvkcH6/x4xPkud9XS2p69ilzAAAAgGMKSn379pVHH31Udu/eneM+R44ckVGjRkmPHj0K4vgAACgyISHF5IqONWXTqIEy2qOwdGvb4tK0yokhv2GhIXJW40rSo2GsNK9WWr656UwZckbNHB/zg2kbpccLU0yDRgAAAMCRPZS0kNSvXz9Zt26dGYXUuHFjKVeunISGhsrRo0dl48aNMmXKFNOcW3sp1atXT5wmkHsoaRQSExMlOjraEQ3EYC+yCFus3nVYjiWnSdOKUXnK45t/rZeXJ6/z2vbNjWdIZ3oq4TTx/gibkEfYgizCJpkBnse81DTyVFBSqamp8sUXX8gvv/wiy5cvl71790pycrKUKFFCGjRoIGeffbbpr1S+fM5TAIJZoBeUdK6nFggDMfgIHmQRwZDHlLQMue3rhfLn6v+mgD8ysLHM27RfujWIlavOrCWhIeQbecP7I2xCHmELsgibZAZ4Hgu1oITgLShpN/oFCxZI+/btA7IbPYIHWUSw5HHrvuPS/cUpPm97eEBjuaWH80by4vTw/gibkEfYgizCJmkBnsdCW+UNAADkXo1y0XJBm2o+bxv1xxpWgQMAAEDAoqAEAEAh0WHOr17W2qwe58snMzfRrBsAAAABiYISAACF7NrOtX1uf2HCWmnw6B9y4+cLJD2DwhIAAAACR556KJUtWzZPTaX2798vThPIPZQCvXkYggdZRDDmUZtxfzh9o5zfupq8Py1Olm0/lG2fz67rID0bVTzNI0Yw4/0RNiGPsAVZhE0yAzyPealp5KlD1J133hmQTwhyLyUlxSxvCPgbWUSw5bFjnXLmos5qXFFembxWPpy+yWuf4V8vkvF3dJPaFYqf1s9CcOP9ETYhj7AFWYRNUhySR1Z5K2CBPEIp0LvRI3iQRTgpj5/O3CQjxq3y2vb04GYy5IxaElLsRB8mwIX3R9iEPMIWZBE2SQvwPLLKGwAAAeK6LnVkyn09vbY98etKqffI79L/tekSt/eo344NAAAAyAkFJQAA/KxOheIy5Iya2bav3XNE+r06TV6auFZW7zrsl2MDAAAACrSgpA23v/322/zeHZbSxmGADcginJbHm7rVlUaVSmbbrqu/vTVlgwx4fbp8NnOTHEtOK/Rjgd14f4RNyCNsQRZhk1CH5DHfPZSWLVsmXbp0kSNHjhT8UQWwQO6hBADwP/1n+adFO+SPFbvkz9Xx2W6vViZaJt7dXUpEBt6cfAAAANitSHooRUZGSnh4eH7vDks/xBw8eNBcA/5EFuHkPGoT7ovaVZePhnaQ724+M9vtOw4mSs8Xp8jCLfslMSW9SI4J9uD9ETYhj7AFWYRNMh2UR3oowS09PV3WrFljrgF/IouwiT/zeGbd8jLhrm4y4rxm0rjyf9PhEo6myEXvzpYmT0wwU+GOJKV63e94Spos3nrATJdDcOH9ETYhj7AFWYRN0h2Ux1wVlJKTkyUlJUUyMjLcF9eTo1U3z+2etx87dqywjx8AgKDWuHIpGdq5tky4q7t8cHU7KRvjPTpYm3V/OWeL17bbvl4kF7wzS275cmERHy0AAACcIlcNGJ566il5/vnnzTD8bA8QdvKHcEJVDgCAotCvWWVpW6us9H55qhxK/G9U0iczNkv3BrEyZ+M+WbD5gPyzdq/Z/ufqPWaKnPZdAgAAAIq8oHTDDTfIoEGDvHombd68WW6++WaZNGmSz/voyCVGKAUWLRhGR0f7LBwCRYkswia25bFCiUhZ9HhfWbnzkDz+ywpZuv2QJBxNlnPenOFz/7u/WyLPXtBcGvpYQQ6Bx7Y8wtnII2xBFmGTYg7KY75XeVu7dq106tRJ9u/fX/BHFcBY5Q0AUFSWbT8o5701M1f7PnN+c7n6zFqFfkwAAAAIXEWyyhuCj/a+io+PN9eAP5FF2MTmPLasXkY+uba9lIr6b8BxycgwM8WtpMc2paOZnvt9taSk2XceCI48wnnII2xBFmGTDAflMVdT3nxJS0szzbo9TZ8+XeLi4uTaa68tiGNDEdPAb9y4UcqVKychIdQa4T9kETaxPY9nNa4kS57oJzqq2nNo9YLN++XKD+dKSvp/v8x8MG2jzNu0X7668QwpEZnvXwHgR7bnEc5CHmELsgibZDgoj3k+O1dfpKioKOnTp4/XbcuXL5dbbrlFvv7664I7QgAAcFIhIcWyzdNvX7ucrBs5QGY/fJZUKBHh3r5k20Fp/uREGbt0px+OFAAAAI4sKI0ZM0bq1asn69atk0qVKpmV37TytnXrVnM555xz5JlnnpHrrrtOvvvuu8I7agAAkCtVSkfL/Ef7SP9mlb223/HtYnnr7/V+Oy4AAAAEtlyPd9dRRzqV7frrr5fatWvLlClTZODAgdn2c/X4vuaaa8x+Z555ZsEeMQqN/nVbm285oRs97EYWYZNgyKMe+yuXtZKqE6Plk5mb3NtfmrROzm1VVVbtPCwfz9gkTauWkscGNZWIsOAenh3IgiGPCB7kEbYgi7BJMQflMVervG3btk3q168vI0eOlPvuu89smzhxotxzzz0yadKkbPsfP35cli1bJhdddJE4Dau8AQBstm3/cen2wpQcb7+2c2156rxmRXpMAAAACNJV3mrUqGEKRK5iktI6VGhoqFSrVi3bpUGDBo4sJgVD87Dt27c7ohs97EYWYZNgy2ONcjEy5b6eUiYm3Oftn83aLJNX7Sny44Iz84jARh5hC7IIm2Q4KI+5HtPeqFEjr++1YsV0tuDipODDbmQRNgnGPNapUFz+vrenDGju3VfJ5aYvFpiRTLBPMOYRgYs8whZkETbJcFAe871mcKdOnczF0759+6R8+fLm65SUFImI+G9VGQAAYI9yxSPk3avaSXpGphxNSpOSUWHS+5WpsinhxGquV388V+rGlpCa5WLkxm51pHrZGH8fMgAAAAJxhNKaNWtk8+bNZjU3vdbvsxaTWrRoIT/88IP5/vbbb5dLL7204I8YAAAUmNCQYlI6JlxCQorJ04P/6520ed9x+XtNvJkC1/X5KbJy5yG/HicAAAACtKDUtGlTqVevntSpU0fq1q0rzZs3d6/opm677TYpWbKknHvuubJx40b59NNPpVevXoV13CgEISEhEhsba64BfyKLsImT8titQayMubWTFI8IzXbbnd8tMavBwb+clEfYjzzCFmQRNglxUB5ztcqb0qls2pi7ZcuW5rpbt27SvXt3GT58uOzYsUMuvPBC6du3r1n97YYbbjD7zJ8/X5yGVd4AAIEu4WiyzIrbJ/M27ZOv5mx1bw8PLSZjbu0sLauXMd/vP5YiZWPCHbEsLgAAgBMcLuhV3pRrRTfPa5369sYbb8j06dPl1ltvlb1798qePXvkq6++kmeeeaYgzgVFSJuGxcXFOaJ5GOxGFmETJ+axQolIOa9VVXn2/Bby5Q0d3dtT0zPlvLdmyq9LdkjfV6ZK22cmy30/LvPrsTqNE/MIe5FH2IIswiYZDsrjaY3Bev/992XMmDFy5513ylNPPWUKSpUqVZLx48dL//79C+4oUSQ08PoaOiH4sBtZhE2cnkedBjf1/p7Zpr+tjz9qvh6zaLsZqYSi4fQ8wi7kEbYgi7BJhoPymO+Ckg5vb9SokfTp00deeuklMyUuISFBEhMTpXPnzuYaAAAEvlrli8v7V7fL8fbVu+itBAAA4DS5LihpsSgiIsKs5qbXOoTr2LFjppD08ccfmwpcVFSUlChRwjTn1utatWqZaXEAACCwnd2ssoy8oLnP24Z8NFfS0n3/FW7nwUT5dOYmGb9sl6TmsA8AAAACT1hud9RmTL/++qsMHjzYXA8ZMkQef/xxiYmJMYWj5557zhSXdHU3XQkuNTXVTHv77rvv5KGHHircs0CB0C701atXd0Q3etiNLMIm5PE/Q86oJZe0qyHr9hyRrfuPy93fL5HktBNForNfmyZNqpSSqev2SmyJSBlyZi1pWqWUXP3xXEnLOLH+R4tqpeWrG86Q0jHhfj6TwEUeYRPyCFuQRdgkxEF5zPUqbxUrVpT4+Hj3dYMGDUz37zZt2kjXrl3ltddeMyOUtNhUv3590xVc+ypdfPHF0ry5779oBiNWeQMAOMW7/8TJ8xPW5Ok+JaPCTFEpbu9RM+qpeGSu/7YFAACAQFzlzZdXXnlFJk2aJCkpKWbE0q5du2T27NnSsmVL2bZtmykoOamYFOjS09Nl9erV5hrwJ7IIm5DHnA3rUVeiwvP2q8SRpDQZ/PZMueeHpTJi3MpCO7ZgRR5hE/IIW5BF2CTdQXk8rabcWkRq2LCh6ZN08803iw52CgsLk7Jly8rtt99esEeKQqevn1YhczloDSg0ZBE2IY8n/11g4WN95eEBjaVNzTJ5vv8PC7bLocTUQjm2YEUeYRPyCFuQRdgk00F5zHVB6eDBg9K9e3f39Y4dO8z2iy66SJKTk6VZs2YSGxtrpsN9++23MnHiRBk7dmxhHjsAAPAznbJ2S4968vNtXWTz6EGy7tkBUr9iiWz7jTivmc/7a7Nu/YUr/nCSI37xAgAACBa5blygjbW1R9LAgQMlIyNDevbsabbrtLbw8BPNNbWfkhacmjRpIsOGDZM77rhDzjnnHEc0owIAACIRYSHy2+1dZfehJNHy0DO/rZJOdcvLNZ1qyYb4o/LlnC1e+z/y83JzcalQIkJ+v7ObVCwZ5YejBwAAQIE35c5t8yZX06a9e/fKtGnTzAgmJwnkptxaKExISJAKFSpQBIRfkUXYhDwWrNoPjc/VfvMe7S2lo8MlPCREQkKKFfpxBQryCJuQR9iCLMImGQGex7zUNAq0oITALigBAFDYPp+1WZ4cm7dm3HVji8sDZzeW/s0rF9pxAQAAQIpulTcEF+1Cv3TpUkd0o4fdyCJsQh4L1tDOtWXOw71l6RP95Paz6stZjSvKZe1ryKfXdpCyMSem0Ge1ce8xGfbVQpmyJl6cjjzCJuQRtiCLsEm6g/KY6x5KCH46WC0xMZGmqPA7sgibkMeCV7n0if5I9/Zr5LV98RP95L4fl8r/Fm73eb8XJ641TcDrVCgusSUjxYnII2xCHmELsgibZDoojxSUAACANUZe0Fyu7VzbFJ0SjibL7d8slvXxR81tq3Ydlkvfn22+/uqGM6RrgwoF+rNnxSXI8xPWyjktqshN3esW6GMDAAAEG6a8AQAAa0SGhUrzaqWlQolIaVy5lEy+p4e8dlnrbPtd9fHcAv258YeT5MoP58rSbQfl+Qlr5FhyWoE+PgAAQLChoAS30NBQady4sbkG/Ikswibk0f8Gt64q13Sq5XPFuKfHrZJ/1p5+b6Xv529zf52WkSnxR5LFRuQRNiGPsAVZhE1CHZRHVnkrYKzyBgBAwdNfV+Zu2i93frdY9hzOXux544o2cl6rqnl+3LT0DBny0Vzz2J5+HNZJdhxIlAfHLJPktAypW6G4fH3TGVKldPRpnQcAAIDNWOUN+ZKWlibz588314A/kUXYhDzaoVixYnJm3fIy6a4eMqB55Wy33/HtYpmSZaSSFqF0Cpv2Ylq09YCc99YMefTn5ZKc9t+qK1PW7s1WTFIJR5Llru+XmGKS2phwTL6YvUX8jTzCJuQRtiCLsEmag/JIU254ccLShggMZBE2IY/2KB0TLu9e1U5+mL9NHhizzOu2r+dskV6NKrq//27+Nnn4p+Ve+yzbfsj0R3rh4lamD9M8H8UkdevXi7Jte39qnFzXubZULHVilTp/IY+wCXmELcgibJLukDwyQgkAAAScSzvUkM2jB8kPt3Ryb/tzdbws3nrAfH0kKTVbMcnllyU7peFjf+RYTMpJRqbIb8t2neaRAwAABAfHFJSmTJkiISEhMnDgQJ+367D4d999V5o3by7R0dHSpEkT+eabb4r8OAEAQO51rFNOLmxTzf39Be/Mkpu+WCBtn5mcp8fp1ShWfh3exedtDSqWcH+9Pv6orNhxSPq8MlVG/b76NI4cAAAgsDmiKfexY8ekRYsWsmfPHlm5cqXUrl072z633XabKSjVqFFDLrroIrPf5MmT5fPPP5drrrnGEU25NQqJiYmmoKa9KgB/IYuwCXm03/YDx+Wqj+bK5n3HT7lvicgwOZrs3dOgVfXS8svwLrLjYKJ0fX6K121xzw2UQ4mp7gKVFrA8RzZd0KaavHpZaykq5BE2IY+wBVmETTIDPI95qWk4oofSgw8+KJs2bZIXX3zRZzHpjz/+MMWkRo0ayezZs6Vs2bJm+5VXXil33HGHDBgwQGJjY8UJIiIi/H0IgEEWYRPyaLfqZWPkk2s7yFkvT81227mtqkrrGmXkn7Xxcl+/RrJy52F5auxKSUnPkBbVSstrl7eWmuVizC98sSUjJaTYialtqlqZaAkNKSZlY8IlJiJUjqekZ5sm9/PiHRK396i8fWVbqVEupkjOlzzCJuQRtiCLsEmEQ/IY9FPepk6dKu+88460adNG7r77bp/7vPXWW+b6hRdecBeT1JNPPmmqcmPGjBGnNA5bsGCBYxqIwV5kETYhj4GhbmwJ+eTa9qY45DKsRz154/LWckPXOvLlDWdIqxpl5MozasrEu7vLy5e0kq9uPEPqxZaQ8NATvw5FhoVKj4b//QGpWdUTf5XTYlP1stE5/mxt9P3h9I1SFMgjbEIeYQuyCJukOyiPQT1C6fjx43LDDTeY3kkffPCBhIaG5lh0iomJMSORPOmIpVq1apmpb8OGDSuiowYAAPlxVuNK5nIqdSoUNxdfdPW3EeNWyuZ9x+Tuvg3d23W00ro9R93fVy4VJbsPJ7m/X7r90GkfPwAAQCAJ6hFKjz/+uMTFxUmrVq3k119/lXvuuUc++eQTU2jynB+oPZa0GXd4eHi2x2jQoIF5DAAAEPx02ttbV7aV327vJk2q/Nc3oFZ57wLUpHu6y9nN/iteHTyeUqTHCQAA4G8BNULpp59+kkWLFp1yPx2VpE2w3njjDfO93sfzfs8//7yZxqZFJC0oqUqVfP9FU6fALVmyJMeflZycbC4ursdLS0szF6UjpPSSkZFhLi6u7ToUzrM3ek7bdYSVDrt3Pa7ndpV1SF1O28PCwszjem53NQvztV0fJ6djt/2cfB0752T/OXn+/GA5p5Nt55zsPifXMbn2CYZzynqMnNOpz+nSdtXkr9V7ZNuBRDOFLiasmLx9RWsZ9OZMWbvnqOw8mCibE47KxJW75axGse4RUAV9Tq7j1GteJ87JlnNy/YxgOqdTbeec7Donz98hsx5joJ5TML5OTjmndI+vA/GcPPcJqoLS2LFjzaprp9KnTx95++23zYunBaHXX39dunXrJgkJCaaf0qeffiqDBw+WVatWuV84nfLmS2RkpNeIpqxGjRolI0aMyLZ98eLFUrz4iV8mtaF3vXr1TGPwvXv3uvepXr26uaxbt870anKpW7euVKxYUVasWGEKYy6NGzeWMmXKmMf2DFTLli1N0y+dp+mpffv2kpKSIsuWLXNv0/Pt0KGD+Xlr1qxxb9cO9Po42rRcH99Fu7s3adJEdu7cKdu3b3dvD5Rz0tFp+rpv3PhfbwvOKTDOSVcU0Pvs2LEjaM4pGF8nJ53Ttm3bgu6cgvF1KsxzeqF7tNRp1E4qlCruPqdKEamyVkRS0zOl50snmoJ/Om29vNqnjPklsLDOSY+L14lz8vc5uR7D9btjMJxTML5OTjinOnXqmOPRlbqD5ZyC8XVy0jk1bNjQHFPWXkqBcE55WZCsWKZnKSpI6AuhH0Z15JBOdTvvvPO8bj/33HPlt99+M7f16tXL7Hv++efLzz//nO2xLrvsMjMyKjU1NdcjlGrUqCH79u1zL7EXKJVb/Zk6/U+LaK4RS1SjOSd/nJPuk5SUJCVKlPAaGRLI53Sy7ZyT3efkyqP+4eFk5xpI55T1GDmn/J/T2t1HZNBbsySrCXd0kfoVSxTKCCXNY1RUlNmX14lz8uc56THqByjNo+t3yUA/p2B8nZxwTvo4+pks68pagXxOwfg6OeWcMjMzTU1Cf3fM7bHbdE5Hjx41A3O0yOSqaTiqoKQVuWrVqplK4a5du8yTlHVVt9tvv91MfXvggQdMJU9H5ixdujTbY/Xs2dOMZIqPj8/Vz9aCkj5ebp582+j/wFop1eqoBhfwF7IIm5BHnMrwbxbJ+GW7sm3XVeYe7N/I/UeagkAeYRPyCFuQRdgkLcDzmJeaRlA25XadtBaJshaTlGu0kauC3aZNGzOE7MiRIz6DUKVKlSI5bgAAEHju7tPA5/b3psbJwDdmSEraib8Grt9zRN79J0627DtWxEcIAABQ8IKyoKTTZOrXr2/6XfgagOUaiaTzDtUFF1xghqR9+OGHXvv9+OOPZgqY9mQCAADwpX7FknJFx5o+b1u967A0fOwPqf3QeOn76jR5fsIa6fHiP5KeEXQDxAEAgMMEZUFJXXXVVWa62yuvvOK1ffr06fL111+b0UvaqFtdd911ZpW3xx9/3PRVUrNnz5Z7773XDFEbOnSoOIVr7ibgb2QRNiGPOJVnz28un17XQd6+sm2u9v9u/tZ8/6zNhzPk7zXxkkFRChbg/RG2IIuwSahD8hiUPZSUjizShtvz58+XHj16mGltmzdvlnHjxpleBuPHj5d+/fp5FZq0Mff+/ftN8yxd2U33e/HFF01hKbcCuYcSAAA4fXd+t9j0VOrXrJLob1l/rNidbZ9qZaJl8j3dJSYib70VdLqcjnByWfBYH6lQIrJAjhsAAOBwHmoaQVtQUrrqxJtvvinfffedxMXFmSqhTnN7+umn3aOTPO3evVteeOEF0zdJG3rfeeedPvcL1oKSRkGPW4+/IBuIAnlFFmET8oj8SExJl+iIE3+dPJKUKl/M3iLjlu6UNbv/69dYOjpcFj3eV0JDcp+rlyaulbembHB/P+K8ZjK0c+0CPnogd3h/hC3IImySGeB5pKDkR4FcUAr0bvQIHmQRNiGPKEjamLvfa9PMyCV1W896cl2XOlKhRESuful86tfl8tns/6bLVS4VJXMe6V2YhwzkiPdH2IIswiZpAZ5Hx6/yBgAAYKMGlUrKY4Oaur9/55846TDyTznnzRkyc0OC9Ht1qjzx6wo5lpzm8/6b9x33+j4Pg5sAAAAKFAUlAACAInRD1zrSr2klr20rdx6WIR/NlXV7jprpcc2enCjDvlzoVVhKSk2X1bv+mzKn4o8ks2IcAADwCwpKcNOh9tHR0QE5zxPBhSzCJuQRheGJc5tKeOjJMzVh5W5TWIo/nGS+f2XyOtlzJNlrn7SMTNl31HsbUFR4f4QtyCJsUsxBeaSHUgEL5B5KAACg6Czffkh+XrxDPpm56ZT7znroLDn3zRmy71iKRISFSPOqpWTR1oPmti9v6Chd6lWQEOa/AQCA00QPJeRLRkaGxMfHm2vAn8gibEIeUVhaVC9tRio9NKCxe9vlHWpI/2aVs+3befTfppikmlaKkf7N/9vn6o/nSd1HfpeJK3cX0ZEDJ/D+CFuQRdgkw0F5DLyW4yg0GviNGzdKuXLlJCSEWiP8hyzCJuQRhW1Yj3rmknU1uL6vTvO5f7mwVLmgdRX5eMYm2XP4v+lur0xaJ2f7KEYBhYX3R9iCLMImGQ7KY3CfHQAAQICuBrfxuYHSq1FsttsalguTsjER8v7V7b22r91zRBLopwQAAIoII5QAAAAspD2RPr2uo6SkZcjsjftk9a7DUjoqVGqm7zK3t65RRlY9fbY0f3KiuBZ6W7B5v/RvXsW/Bw4AAByBEUpw0y702nzLCd3oYTeyCJuQR/ibNuHu0TDWTIu7tH0NKVe2jDuPMRFh8tIlrdz7vvtPnLDeCooK74+wBVmETYo5KI+s8lbAWOUNAAAUpeMpadL3lWmy42Ci+f7KM2rKE+c0lajwUPc+x5LTpHgkA9MBAMDJscob8t08bPv27Y7oRg+7kUXYhDzC9jzqKKXLOtRwf//N3K3S++Wp8vvyE1PjHv9lhTR/aqK8888Gvxwzghfvj7AFWYRNMhyURwpKcGTwYTeyCJuQRwRCHptV9f4Loo5Wuu3rRTJ13V75cs4W0fHoL0xYW8RHi2DH+yNsQRZhkwwH5ZGCEgAAQIDr2qCCtKxeOtv2oZ/M8/r+aHKaHElKpc8SAAA4bUymBwAACHCRYaHy6/AuZrW3bfuPS8+X/vG53xUfzJHlOw6Zr3s1ipW3h7Q1U+YAAADyihFKcAsJCZHY2FhzDfgTWYRNyCMCJY+6mkxoSDGpXaG4PNi/sc/7u4pJasravdL0iYmyYPN+iT+SVKjHjeDE+yNsQRZhkxAH5ZFV3goYq7wBAAAbPPzTcvl23tZc76+rwz13QYtCPSYAAGA3VnlDvmjTsLi4OEc0D4PdyCJsQh4RqHl88tym8sm17WXeo73l+YtOXSjS1eFqPzTeXGasTyigI0Yw4/0RtiCLsEmGg/JIQQluGvi9e/c6IviwG1mETcgjAjWPUeGhclbjSlKxZJRc2La69GgYa7aXiQmXn2/rLNd1qS3hocV83veqj+dK31emysIt++XmLxbIA/9bKoeOp/rcN10bN8GReH+ELcgibJLhoDzShREAACDIhYeGyOfXdzSru2mvJdWmZll58txmZlv/16bL2j1HvO6zPv6oXPTubPf3PyzYLrd0ryvVy0ZL3N5jUiIyTMJCi8lrf66XiNAQWfX02RIWyt8qAQBwCgpKAAAADuEqJmXdNuGubjJ51R75aMYmmbdpf473f3/aRp/bU9IzpP6jf0ipqDAZc2tnaVCpZIEeNwAAsA8FJbhpF/rq1as7ohs97EYWYRPyCCfkUYtK/ZpVlr5NK8mirQflnh+WyJZ9x/P8OIeT0qTvq9OkVfXSUi+2hDwyqIlUKBFZoMcKe/D+CFuQRdgkxEF5ZJW3AsYqbwAAIBgcTkqVP5bvks9nbZFVuw7n+3Ha1yorj5/TVFrVKFOgxwcAAPxb06CgVMACuaCUnp4u69atk4YNG0poaKi/DwcORhZhE/IIp+dx39Fk+X3FbulWv4Js3ndMNu49Jhe1rS6jJ6yRdXuOyGuXtZYXJ66VsUt3nvRxosJDZM7DvaVMTESRHDcKH++PsAVZhE3SAzyPealpMOUNblpb1NBQY4S/kUXYhDzC6XksXyJSrj6zlvm6doXi0rPRie2jLmzh3ueNK9qYwtK6+CPy3O9rZNq6vdkeJyk1Q1o/PVkublddXriopYSE+F5hDoGD90fYgizCJpkOyiMFJQAAAJw2LRA1rlxKvvh3Nbm/18TLz4t3yG/Ldnnt97+F22XG+gT54ZZOUrN8jN+OFwAAnJ7g7xIFAACAIqVNvns3qSRvXdlWNo8eJDd2reN1++7DSdL9xSmycMsBvx0jAAA4PRSU4KZd6OvWreuIbvSwG1mETcgjbBKoeXygf2NpULFEtu0XvTtLmj4xQR7/ZYWkZ2TKkaRU2RB/1IxwSkxJl9f+XCe3fb3Q9GqCfQI1jwg+ZBE2CXFQHmnKXcACuSk3AABAYdp+4Li8PWWDfDtvW7bbQkOKmaKSCgspJmn/fq2ql42Wqff3MvsAAAA7ahrBXzJDnrrRL1261FwD/kQWYRPyCJsEeh6rl42RURe2lD/v6Z7tNlcxSXkWk9T2A4lS/9HfpfZD46X5kxPl81mbzfbU9AzJyLIvik6g5xHBgyzCJukOyiNNueFmhpcnJjqiGz3sRhZhE/IImwRLHutXLCnrnh0gew4nydilO+XlSWvlVHUh1ykfTU6TJ8eulKfGrXRv61K/vAxsUUWu7FjT9G9C0QiWPCLwkUXYJNNBeaSgBAAAgCIXERYiNcrFyPBe9eXS9jVMg26dEte1QQXZeTBRVuw4LL0aVZRp6/fK0m0HZdKqPV739/w9feaGfeZyKDFVbu1RT1LSM2Tepv3SvGppKVs8ouhPDgAAB6CgBAAAAL+KLRkp/ZtXdn/fuHIpOatxJfN1i+qlzXVSarq8MnmdfDBtY46P88KEtebi0qRKKfnt9q6SnJYuMRH82gsAQEGiKXcBC+Sm3BoFPW49foaLw5/IImxCHmET8vjf83DgeKpMW7dXnvh1hRxOSjvp/trM++VLWsn5baoV2TE6AXmELcgibJIZ4HnMS02DglIBC+SCEgAAQCDSXkxnPPfXKffbNGpgQP5yDwBAUWGVN+RLWlqazJ8/31wD/kQWYRPyCJuQR98qlYqSzaMHycoRZ8u8R3vLrT3r+dxPV4fTqXMuOsKp/2vT5IUJa7y2I3fII2xBFmGTNAflkcnk8OKEpQ0RGMgibEIeYRPymLPikWHm8mD/xtKnSUW56N3ZXrc/NW6VubSqUUZu7lZXhn+zyGxfs/uIHE9Jl6fOa+anIw9c5BG2IIuwSbpD8sgIJQAAAASddrXKmVFLz13QItttumqcq5jk8tmszXI8pWD+mnzweIrE7T1aII8FAICtKCgBAAAgaF15Rk355sYzpGTkqQfmN31ionQe9ZeZApdwNDlfP+9wUqoMemOG9H55qpliBwBAsKIpdwEL5KbcGoXExESJjo6mYSX8iizCJuQRNiGP+bfjYKIs23ZQ3p0aJ8u2Hzrl/lVLR8lVnWpJldJRMrhVNQkJOfnzPTtunxmV9NgvK7y2v355axncOjhXlyOPsAVZhE0yAzyPrPLmR4FeUNK5nqGhoQEZfAQPsgibkEfYhDyevrT0DFm87aCkpmXImXXLy9LtB+WCd2ad9D6jL2whl3esmePtq3cdlgGvT/d5W5mYcFn8eF/ztes109fxcFKalI4Ol0BGHmELsgibZAZ4HlnlDfmioV+wYIFjGojBXmQRNiGPsAl5PH1hoSHSoXY56Vy/ghl11KZmWdn43EBZ80x/WfpEP/nk2vbZ7vPQT8tl75ETU+C27DsmhxJT5fv5W6XvK1Pl1yU7ZNzSnTn+vIPHU6XOw7+by6M/LzcfNC5+b7a0fWayvDhxjfk+UJFH2IIswibpDsojq7wBAADA0bSwFBUSKlHhodK9Qaw0rFRC1u3xbqrd88Upciwl+4eDO79b4vsxi4lkZKkVfT13qzSpUkoWbjlgvn97SpyUiAyXW3vWO+WoqiNJaVK2eETeTw4AgEJCQQkAAADwGME07vausnz7IZm8ao+8P22j2e6rmJSV9luacl9PU5jSItAPC7bL07+tlKTUDPc+WXssPT9hjem9VL5EhNzbt5FEhHlPINARTDd9sUCmrN1rvh/3f12lRfXSBXS2AADkH1PeAAAAAA+RYaHSvnY5eXhgE6lboXiu7lO+eIR8e9OZppjkKkzpCnO/3d5NHh3Y5KT3/d/C7fL+1I3y3tS4bLeNWbTDXUxS5741Q36Yv03Ssw5/AgCgiNGUu4DRlBs4fWQRNiGPsAl5LHo/Ltgm9/9vmfv7j65pL1XLRMvuw4nSukZZWbnzkBmZVC+2xElfk0krd8vNXy485c/7857u5vFjIsLkeEqadBn9txw4nupz39kPnyVVSkeLv5BH2IIswiaZAZ5HVnnzo0AvKAXy8oYIHmQRNiGPsAl59I/1e47IlLXx0qdJJakbWyLfr92LE9fKT4t2SOsaZeTRQU1k4BvTTW+knOhLfKrf1P+8p4fUr5i/Yzpd5BG2IIuwSWaA55FV3pAvWkVdtmyZI7rRw25kETYhj7AJefSPBpVKys3d6+W7mKT0Q8UD/RvLnEd6y3tXt5Ma5WLkpUtaSasaZeSMOuV83sezmDTqwhamoJXVVR/NlQw/TX8jj7AFWYRN0h2UR5pyAwAAAH5wdrPK5qJemrhW3pqywed+9WKLy2Xta8gVHWuav3wv2npQLnp3lrlt9+Ek+XjGJrmpe90iPXYAABihBAAAAPjZ1Z1qSaNKJX3e9vTg5hISUsw90qldrbKm4bfLyN9XS+2HxkurEZNk/LJdRXbMAABnY4QSvGjjMMAGZBE2IY+wCXkMTpVKRcnEu7u7v9+UcEzenrJBujeMlS71K2Tbf+T5zWX+pv2yPv6oe9uhxFQZ/s0imbCyqjx7fnMpHR1e6MdNHmELsgibhDokjzTlLmCB3JQbAAAAgeO3ZTvl/75ZnOPtV3SsIaMubFmkxwQACGw05Ua+aG3x4MGD5hrwJ7IIm5BH2IQ8wtOgFlXkvn4NpWX10j5v/3beNvl81maZuSFBNniMZDoVbfK9Zd8xSUvPOOl+5BG2IIuwSaaD8khBCW7ahX7NmjWO6EYPu5FF2IQ8wibkEZ60n9L/ndVAxv5fV9k0aqD8MrxLtn2eHLtShnw0V857a4bE7c1eVNJpcg/+b5mM/mONJKWmy7LtB6XuI79Ljxf/kfqP/mG+33sk2efPJ4+wBVmETdIdlEd6KAEAAABBUFxqXaOMbB49yBSGGj8+wev24ynp8tWcLfLQgMby7dytZkW5DrXLSfyRZFm45YDZ572pcdke97y3Zprr+89uJMN71Zf0jEwJ/bdBOADA2SgoAQAAAEEkKjxU1j7bX1o8OUlSPKatfTpzs7m4/LFid64f88WJa83FZc7DvaVCcT5KAICTMeUNXn/Zio6ONteAP5FF2IQ8wibkEbkVGXaiqPT65a3zdf9TDUIa+sk8OZaSTh5hBd4bYZNiDsojq7wVMFZ5AwAAgE3W7D4sH0zdKMt3HJL1Pppzd6hdVno3qSS7DiZKtwax0qxaKalSOlr2H0uRFyeuMc29fbmlR115eECTHBt7hzA1DgCCuqZBQamABXJBKSMjQxISEqRChQoSEsLgNfgPWYRNyCNsQh5xupLT0mXrvuNSrWy0XP3xPNlzOEm+uL6j1I0t4XN/7Zn0yYxNkpaRKY2rlJTtBxLl8V9WmNsiQovJzze0lI/nJ0hqRqaMOK+ZlCseIf+sjZfhXy+SdrXLycdD20t4KFlF4eK9ETbJCPA85qWmwcRneAV/48aNUq5cuYAMPoIHWYRNyCNsQh5REFPhGlQqab4ec2tns6z1yaZlaAPum7rX9do2b9N+Gbd0p6SkZ8qgD5a6tx88niKfX9dRPp6xyUyHm7Zur3wzd6sM7Vy7EM8I4L0RdslwUB6D++wAAAAA5Cg/PT461i7rc/v09QnS//Vp5trl58U7Tuv4AAD2oqAEAAAAINcu61BTbskyasll3R7vHk1Lth00o6AAAMGHghK8/kKlcyWd0I0ediOLsAl5hE3II2wQERYiDw9sItPv7yFXty4rvRrFStmY8Bz3/2be1iI9PjgP742wSTEH5ZGm3AUskJtyAwAAAPmhHykufX+2zN98wOft0x/oJTXKxRT5cQEACq+mwQgleDUP2759u7kG/IkswibkETYhj7A1j/qX+C9vOEPeu6qdTLyru8x7pLd4/nH+lcnrZNaGBHnnnw1mGhxQkHhvhE0yHJRHCkpwZPBhN7IIm5BH2IQ8wuY8RoWHSv/mlaVR5ZJSsVSUWUXOszn3lR/NlRcmrJXz354pg9+aIRvij/jx6BFMeG+ETTIclEcKSgAAAAAKXOvqZaRUVJjP25ZuPyQPjVle5McEACg4FJQAAAAAFLiQkGLy/EUtpVPd8jKgeeVsty/YckBqPzReur8wRe75YYnsP5bil+MEAOSP7z8ZwJFCQkIkNjbWXAP+RBZhE/IIm5BHBFoeB7SoYi4qKTVdvp23VUaMW+W1z9b9x83lp0U7ZM0z/c3UOSAveG+ETUIclEdWeStgrPIGAAAA5Ew/frR+erIcSkz1efu8R3tLxZJRRX5cAABhlTfkjzYNi4uLc0TzMNiNLMIm5BE2IY8IhjzqinCzHz5LrutSWzrXK5/t9o4j/zJT4V6YsEaOp6QV4BEjWPHeCJtkOCiPFJTgpoHfu3evI4IPu5FF2IQ8wibkEcGSx5iIMHny3GbyzU1nym+3d/W5zzv/xEnTJybKhBW7c/24x5LTZMraeApRDsN7I2yS4aA80kMJAAAAgN80r1Za1o8cII0fnyDpGdm7cQz7aqGEhxaTNjXLypZ9x2TP4WR5/JymckPXOl77zY7bJ1d8OMd8fWHbavLKpa2L7BwAwIkYoQQAAADAr8JDQyTuuYGyefQg+eL6jtluT03PlHmb9ptiknrmt1Vy6fuzzWiko8lppuH31R/Pde+vDb5PZeaGBPlyzhZzXwBA3jFCCW7ahb569eqO6EYPu5FF2IQ8wibkEU7IY/eGsbLsqX5y7pszZMu+4znupwUmvVQuFSU3d68raVlGN93zwxK5vksdMwIqa1Pw7i9OkW37E833R5JS5bae9Qv0HFC0eG+ETUIclMegPsNVq1bJ4MGDpVq1ahITEyMNGzaUBx54wHQrz0r/YXn33XelefPmEh0dLU2aNJFvvvlGnMRJwYfdyCJsQh5hE/IIp+SxVFS4jP2/rjLyguYy4a5ucmn76jnuu/twkjz926ps23WU0jlvzpAhH82RtPT/epms3HnYXUxSPy7Ynqdj088Nczfuk12H/nsM+BfvjbBJiIPyGLRnuHHjRunatavMmTNHzjnnHLnpppukbNmy8uKLL0qPHj0kOfnEcFmX4cOHy2233WaWyBs2bJjUqFFDhgwZIl988YU4RXp6uqxevdpcA/5EFmET8gibkEc4KY+lo8NlyBm1pHHlUvLCxa3MdLhNowbKX/f2kMiw3H+Mmblhn1z47izTn0mnt+nIJU8padkb5+p+2/Yfl50HE7NNiftk5ma57IM50mnU33LLlwt89n1C0eK9ETZJd1Aeg3bK21NPPSWJiYmyePFiqVWrlnv7rbfeKu+99558++23cu2115ptf/zxhxmd1KhRI5k9e7YpPKkrr7xS7rjjDhkwYIDExsZKsNO/tujoLb0G/IkswibkETYhj3B6HosVKyb1YkvI2mcHyMHjKdJx5F+S8u/oo671K8gz5zeXga9Pl8QsRaBl2w9JvUd+l6qlo2TnoSSv23YcTDRFpvNaVZX2tcuZVeUe+2W5JKWeeNymVUrJo4OayMczNsmA5pXl5Ulr3feduHKPvDNlg9zeu0GRnD98470RNsl0UB6DdoTS/PnzzfQ1z2KSGjRokLlet26de9tbb71lrl944QV3MUk9+eSTJghjxowpsuMGAAAAcGplYiLk7/t6SKe65aVl9dLywsUtpU6F4vLBNe0kKtz3x5ysxSTP6XHXfjpfmj85Ue77cam7mKRW7TosQz6aK3+viZf7/7dMjqd4F6tenrxObvx8gVmBDgCcJGhHKBUvXlw2bdokSUlJEhUV5d6+fPlyc127dm33tqlTp5oeSzoSyZOOWNKC1OTJk800OAAAAAD2qF42Rr69+Uyvbd0axMq0+3uZryPDQ+W9qXHy7j9xXvvUKh8jV59ZS54dv7pAjuPP1XtkwZb9MuXenpKanmFWrStbPKJAHhsAbBW0I5SuuOIK2bdvn5nWtmXLFjly5IgZaTR69Ggzfe3CCy80+2nPpGPHjpnRTOHh4dkep0GDBhIX5/0PULDSpmF169Z1RPMw2I0swibkETYhj7CJzXmsWCrKXLQP04P9G8sX13d031asmJhtV3SsKee2qirhocV8PsYdZ9U3DcGjw0Pd28rGhEtoyIn9z2lZxWv/g8dTpc0zk6Xjc3+Z69oPjTeXR35eLvGHfY+MQvBnEc4T4qA8FssMoIl9P/30kyxatOiU+91www1mBNKDDz5omnB7atu2rXz99dfSuHFj8/327dtNA+5zzz1Xxo4dm+2xLr30UpkyZYrs3bvX58/S5t6eDb61QKWPp8WsUqVKmW0aJL1kZGSYi4truzbr8nwZctoeGhpq5o2npaV5HYNuV1mbfuW0PSwszDyu53Z9XN0/6zHmtJ1z4pw4J86Jc+KcOCfOiXPinALtnNbsPmoqSk2rlMx2TmOX7pIN8UdkYPPK0rBSCff2jQnHZdm2A9KrUQUpGRUuiSnpkpiWaQpWvyzaJnf9sExOpXrZaPn73h7yx/KdsvtwslzbqZYpTPE6cU6cE+dk2zkdPXrUtALS9j+umkZQTHnTgs/nn39+yv369OljRh19//335vvo6GgzBU6LPNpt/aOPPjL9kvTJc71wOuXNl8jISDl+/HiOP2vUqFEyYsSIbNu1Gbj+TKUjourVq2em4HkWpnQpQb1oPyd9sVy0mlmxYkVZsWKFaSzuokWwMmXKmMf2DFTLli0lIiJCFixY4HUM7du3l5SUFFm27L9/5PR8O3ToYH7emjVr3Nv1OdJRWtp7SsOkYVSlS5eWJk2ayM6dO03xzSVQzqlVq1aSkJBgVv1z4ZzsPyfNoBZqu3XrJrt27QqKcwrG18kp56R51FGueoz169cPinMKxtfJKecUHx9v8liyZEnzB6xgOKdgfJ2cck5r1641+2se9XfHQDonnYGQ9ZzOb1PdfFY4tG2NLNj23+tUv2JFObYrTtau2OF1TiJRUi19t3x1Xjm57rf94tF2KZvtBxKl4WMT3N+P+mOt3NC6hFxxVjupEJHm85w2bt8te3ds4ffyXJyTDibYs2eP+TdbW54EwzkF4+vklHPKzMw0x9OuXbuAPKe8LEgWUCOUcktPqWnTprJhwwazotvQoUNNZU//gbjxxhtl1qxZpgj0xBNPmF/KtOp2/vnny88//5ztsS677DIzMio1NTXoRyjpNi0o6Sgu132p3HJO/jgnvV1HI+obqOv4A/2cTradc7L7nFx51F8K9BeAYDinrMfIOQXOOenvI5pH/bdap+oHwzkF4+vklHPS34FdedT7O/l1em/qRnn7n41SJiZcbu5eV1bvPCT/W7RDMnLxSevNK9rIgGYV3d+npmfKhe/NkdW7DkvfJhXl3SFt/HJOgfQ66T6axTZt2riPK9DPKRhfJ6ecU7rHZ5msgm2EUlAWlGbOnCldu3aV22+/Xd544w2v2w4cOCDVqlWTKlWquHsjaSVPq9pLly7N9lg9e/aUVatWmb8I5oYWlPTxcvPk20b/B9ZKqVZHNbiAv5BF2IQ8wibkETYhj948R/m7HDqeKq2ennTS+5WMDJNxt3c1Xx9JSpPbvlko2/b/N3pj4WN9pHyJyEI66uBAFmGTtADPY15qGoF3drmwbduJMarNmjXLdptW2rSgtHXrVvc2rWTPnj3bPYQ8axB0eBgAAAAA5CRrMUmVjgmXeY/0lllx+6RSqShpW6uMjF2yU+7/33/TWo4kp0nPl/7J8XE3JhyjoATASkHZdrxSpUrmWqe8ZaVzBjdv3iwVKlRwb7vgggvMfMUPP/zQa98ff/zR9GLSnkxOoMPjdP6q5zBRwB/IImxCHmET8gibkMfc0ebd57epJp3qlZfIsFC5pH0N2TBygEy5r6fUKu+7j6unuPij5jo1PUP+XrNHNiUcK4KjDixkETYJdVAeg3LKm05P01FIJUqUMI28tbGv2rJli9x8880yadIkuemmm+SDDz5wD+lq2LChGaH0zTffyODBg82IpYsuusgUoBYuXGiaZwX7lDcAAAAARWfFjkMy+O2Zkp6l2VKFEpGScPREn9buDWOlYcUS8tGMTe7bL2lXXeZv3i81ysXIixe3ksqlo4r82AEEp7zUNIJyhJJ2WX/wwQfl4MGD0r17dzPNTTuVa58kLSbpCCbPldn0SdLRSFFRUaY5t67O1rlzZ9m9e7eMHj0618WkQKdT/LQpd9ZmaEBRI4uwCXmETcgjbEIeT1/zaqXl+YtaSnR4qPRuXFGWPNFXNo8eJL/fcaKnkpq2bq9XMUn9uHC7bN53XKavT5Bnxq8SpyOLsEmag/IYlAUl9eyzz5rRRjo6STuZa3FJG3FfffXVMmfOHPO1J91v5cqVcvfdd5uVfHR00tSpU+Xee+8VJ8naVR7wF7IIm5BH2IQ8wibk8fRd3K66rHr6bPn42g5SJibCPU1OV4sLDcnelymr8ct2SfyRJHE6sgibpDskj0HZlNvliiuuMJfcqly5srzyyiuFekwAAAAAcKqG3o8MbCI3dqsjj/+yQiau3GO2talZRhZvPZht35U7D0vFRkx7A1C0grqgBAAAAACBqmLJKHlnSDv5YNpG872OWsrIzDQ9l3S1uAfGnFgtbsX2Q9KrUUU/Hy0ApwnKptz+FMhNuTUKiYmJEh0d7fOvJEBRIYuwCXmETcgjbEIe/Wvb/uPS7YUp7u/H39FV6sWWkKjw4F9ZKiuyCJtkBngeHd+UG/kXEXFi3jbgb2QRNiGPsAl5hE3Io//oCm91Y4u7vx/0xgzpNOovU2hyIrIIm0Q4JI8UlODVOGzBggWOaSAGe5FF2IQ8wibkETYhj/736MAmXt8fOJ4qH2dZEc4JyCJsku6gPFJQAgAAAIAA1LtJJbmsfQ2vbZ/N2iwrdhzy2zEBcA4KSgAAAAAQoJ4+v5l8fn1H6dEw1r3t3LdmyKg/VkvC0WS/HhuA4EZBCQAAAAACVGRYqCkmPXt+c6lUKtJs02WX3p+6Udo/+6f8vHi7aRKsK8MBQEFilbcCFuirvOk8z9DQ0IDsRo/gQRZhE/IIm5BH2IQ82udocpo8+vNy+XXJTp+314stLu9f3V7qVywhwYQswiaZAZ5HVnlDvqWkpPj7EACDLMIm5BE2IY+wCXm0S4nIMHn98jby3lVtfd4et/eY9Hllqnw5Z0uB/LxdhxJl5c5DkmHB6CeyCJukOCSPFJTgplXUZcuWOaIbPexGFmET8gibkEfYhDzaq3/zKjLlvp7Su3FFn7c//ssKmRWXIB9N3yiLtx6Q+MNJsnDLAdmUcMzn/r4mtUxauVs6jfpbBr0xQ+o+8rspUh045p8P0WQRNkl3UB7D/H0AAAAAAICCVadCcfn42g5yOClVHv5puYQWKyZjl/43Fe7KD+f6vN/rl7eWwa2rub//bt5Wefq3VZKWniktq5eWW3rUk00JR+W539dkK1LppU3NMuZnX9u5trSsXqYQzxCAv1FQAgAAAIAgVSoqXN6+8sQUuCplokyz7pO587sl8ufqeHnhopby0qS18vGMTe7bFmw5IAu+WHDS+y/eetBcflq0Q96/up2c3axyAZ0JANsw5Q1etHEYYAOyCJuQR9iEPMIm5DGw3HFWA2lb89SjhsYt3SlNnpjgVUzKSWhIzk2Hb/lyoXmMolgHiizCJqEOySOrvBWwQF7lDQAAAEDwO3Q8VZZuPygd65STtIxM0/tICz+fzdrsc/8+TSpKv2aV5b1/4mSjR5+lB/s3llt71jNf/71mj8zffEC0vvT2lLhsjzHm1k7Srla5QjwrAEVd06CgVMACuaCkUdDj1uMPxOUNETzIImxCHmET8gibkMfgM3fjPhn+zWJJOJrs3vbRNe2lT9NKXq/7qV5vvX/7Z//M8fa7+jSQu/o0dI9cyvp4Ow4myrJtB6VW+eLStOqpP1ORRdgkM8DzSEHJjwK5oJSWliYLFiyQ9u3bS1gY7bXgP2QRNiGPsAl5hE3IY/Batv2gLNpyQAa1rCqxJSPz9Rg6Yun6z07eb8mlWplod6+lT2Z6T7NrVrWUfDS0vVQpHZ3j/ckibJIW4HnMS02DHkoAAAAAADddne3aLnXyXUxSZzWuJGuf7S/vXdVWmlc7+YdSHZGkhaSsxSS1cudhufyDOZKSlpHvYwFQOAKvXAYAAAAAsF5kWKj0b17FXJLT0kXnxrw9ZYN8NH2TJKam5/pxtuw7Lg0f+0PmP9rntIpcAAoWBSW46fzO6OjogJznieBCFmET8gibkEfYhDwir8UldW+/RnL7WQ3k05mb5Ku5W2RYj3oyaeUembpur7m9ToXick7LKjKgeRXTKHzMou3ux+gw8r++TC9c1FIu7VDDfE0WYZNiDsojPZQKWCD3UAIAAAAAf9h7JFlKRoVJVLj3cuszNyTIkI/m+rzPpLu7S8NKJYvoCAFnOExTbv8J5IJSRkaGJCQkSIUKFSQkhPZa8B+yCJuQR9iEPMIm5BFFZfyyXTL8m0U53j60Uy0ZdkasVKoYa7J4PCVN3p+60fRf2nUoUQ4npcr1XerIdV3qSGp6hhxJSpOyMeGOGEGCopcR4O+NNOVGvoO/ceNGcw34E1mETcgjbEIeYRPyiKIyqGUV2TRqoIy+sIWEhWQvAn0+e4s8+etydxY/n7VFXv9rvfy5eo8pKm3bnyjPjl8t8YeT5PrP5kvbZyZLn1emmuKSNvv+v28WyQ2fzZdDx1PNku/A6chw0HsjPZQAAAAAAFbT0USXd6xpLn8s3yW3fu09YmnSpmRpP/JvGd6rvrwyeW22+6dnZMpjv6yQ6esTzPdxe49Jg0f/kLoVisvGhGNmW6unJ8ng1lXltctaM3oJyAVGKAEAAAAAAsaAFlXkqXObSt3Y4lK7fIx7+8HEVBn5+2pJTT8xyqhkZJi8M6St+/ZJq/ZkeyxXMcnl1yU7pc7Dv8tkH/sC8EZBCW5ahde5klTj4W9kETYhj7AJeYRNyCP86doudeTve3vKlPt6yqXtq2e7vWPtcvLbHV2lTc0y+Xr8O79bLPuOJhfAkcJpijnovZGCEtxCQ0OlSZMm5hrwJ7IIm5BH2IQ8wibkETbQD+0vXNxKrjyjpntbnyYV5asbz5Ba5YtL5VJRZlqbS9MqpWTDyAHy4TXtvR7nt9u7SrOq/zUgPp6SLnd9v6SIzgLBJNRB742s8lbAAn2Vt507d0rVqlUDshs9ggdZhE3II2xCHmET8gjbsrjxeITsP5ZqmniHh/6XyU0Jx2Tiyt1SIjJMzm9TzVy7+ippY+6o8BMf/I8lp8l1n82XeZv2u+8b99xACfXRCBwI1vdGVnlDvoO/fft2R3Sjh93IImxCHmET8gibkEfYlsXOdcuZgpFnMUnVqVBchvWoJ1edWctdTFJaKHIVk1TxyDB55dJWXvf9azW9lJA3GQ56b6SgBAAAAACAiFQrE+31/c1fLpSXJq4VJvYA2VFQAgAAAADg355Ma57p79V36a0pG2TA69P9elyAjSgowU3nd8bGxgbkPE8EF7IIm5BH2IQ8wibkEcGaRZ0G9/0tnaSkx/S4NbuPSO2Hxsvnszab3ktATpz03khT7gIWyE25AQAAAAAnrNhxSM55c0a27ff1ayj/d1YDWbfniLz25zpTgPpp0Q65qG11efK8plIqKtwvxwsUBJpyI1+0aVhcXJwjmofBbmQRNiGPsAl5hE3II4I9i82rlZZNo/6/vfsAj7LKGjh+IAmQ0BKQTqhSBREIRaUpwtIW5ENdAT9RQNqyIGJbFFxZAbGzLqKCig1FQYoK7lKkKSJI7733KpBASJjvOffbmZ1JJmEmJMydmf/vecaQd+68897kmMycnHtuO2lfu5TH8XELdshnv+yT1m8ukTkbjppkkpq++qB8vepgtl4Dgs/VMPrZSEIJLhrwJ06cCIvAh92IRdiEeIRNiEfYhHhEOMSi9lQa372efNyzoevYlVSHPD9zo9fxf/9us/x701GaeIexq2H0s5GEEgAAAAAAmWhetZj0uL28T2N1Z7iKf50jz83YIKcvJuf4tQGB8t8uYwAAAAAAwKu+zSvL/tOJsvvkRdl3KlFi8kSYyqV65eKkzyerZMHW4x7jP1+x39xaVi8uBfJFSq8mFeXWsrEBu34gu5FQgot2oS9btmxYdKOH3YhF2IR4hE2IR9iEeES4xWLp2Gj56NH/Ln1zp8viZq89LJ+v2CfrDp7zuM+ZaNIm3wuGtsjRa0Tg5Q6jn43s8pbN2OUNAAAAAMKXvsVuO26pbD16Pt19S5++S+KLxATkugBfsMsbsiQ1NVW2bNliPgKBRCzCJsQjbEI8wibEI2xhWyxqI+/JjzaUJjffJAnl46Rmqf++KW/6yo9yNpG+SqEs1bJ4zEkklOCRSdcsJEVrCDRiETYhHmET4hE2IR5hCxtjsWThfPJZ70Yyrf8dMqpzLY/7Ji3dE7DrQnjGY04hoQQAAAAAQA6pXaaw5Iv671vv7zcckePnL5ld4CYs2iVXr4Z+4gGhiYQSAAAAAAA5JDIit8wb0tz1+Z6TF6XhqAVmB7ixP2yVSsPmyNFzlwJ6jUBWkFCCi3ahr1SpUlh0o4fdiEXYhHiETYhH2IR4hC2CIRa1EfdHjzbI8P7GYzTBtM/rfalUMAWV3EEQj9mFXd6yGbu8AQAAAAC8+cObS2TbsfS7vzltGdlGovNEmH8f//2SNBy9wPy7bFy0fNCjgVQrWfCGXSvC0+/s8oas0C7069atC4tu9LAbsQibEI+wCfEImxCPsEUwxeILHWu6/p3/P4kjdzVG/CAjv90sC7cek9tfXug6fvBMkry7eFeOX5/WmwybsUGqD58rX/66P8efLxSlBlE8Xq/IQF8A7KE/PJKSksKiGz3sRizCJsQjbEI8wibEI2wRTLF4R+WbZOOLf5DoqAiJyJ3LHFuy/YQ8/OGvrjEf/rTH3NKaseaQ/LrntCx9+i7J/Z/HZoe35m+XWWsPy4gONeVySqpMWfH/iaTRc7bIAwnx2fpc4cARRPF4vahQAgAAAADgBimQN9KVTFLNqhaT1+6v49NjD51NMk28+3yySk6cv+y139L8zcdk+3+W1X2wbI/cMWaBVHj2e7n7tUXyw8ajHuO1Qfhb83eYj49OXin9Plvtuu/3Syly3O05DpxOlKTk0K+6ge+oUAIAAAAAIIDuq19WYvJEyMApq8W9B/ctpQvJgw3iZfisTR7j/735mLmtGNZSihfMK4fPXZInv1onGw+dk/OXU7w+x+6TF6XfZ7/JO93rSbvapeTMxWR5Y972TK+r4z+XyeyBTeTNedtl6qoDki8qt6we3kpi8pBKAE25s10wN+XWUNDr1uvPlYuyRgQOsQibEI+wCfEImxCPsEUoxeK5pCsmaZM3MkIOn02SmwrkFS1mGjF7k2spWnYoXzRG9p1KzNJjSxfOJz89e3fQf61ziiPI49GfnAYJpWwWzAklAAAAAICddInbV6sOmKoiXdqW3RpXKmKWtJWOjZaWNUrIk1+vy3Cs9nHScUfOJUmxgnnNsYuXUyUuJiookyjIWk6DOjW4pKSkyJo1a6Ru3boSGUloIHCIRdiEeIRNiEfYhHiELcIlFjVx8+e7bpYBLSrLczM3ytSVBzJMLMXGREn9cnGm4qlogTzSvVF5U+3U7h9L042tWqKAzPpzE4lOs+ucVkhltCROE1tvL9yZ7ni9crEy5bHGki8q/Q524SIlTOJRhfbs4Ldw2NoQwYFYhE2IR9iEeIRNiEfYIpxiUSuARneuLaPurSXJqVdF1xwt33VKqpcqKCUL5cu0QmjV8/fIs9PXy7qD50wPpfsT4uX59jXSJZPUoJZVzNK4wV+uNZ/rLnAjv9ts/u0tmaRW7z8r1Yf/IOWKxMi0frdL8UL5JBylhkk8klACAAAAACDIaOJIey2pu6oX9+kxWqU0qUcDn5+j021lzE0dP39JXv/3Nrnow05v+08nyss/bJU3Hrgt3X3rDpyVhVuPS/dG5cI24RQqSCgBAAAAAIBMFS+YTxY+2cLsLvfL7lPyr41H5bFmlSShfJy8v2S3rNhz2mP8N6sPmaVvIzveImeTrpjleXkickun8T+Z+8ct2PH/Hx+8zZW0QnChKXc2C+am3BoKSUlJEh0dTSM1BBSxCJsQj7AJ8QibEI+wBbFoh7OJyTJx6W4Z/+Muvx/7ZZ/G0rhSUQkFjiCPR3Z5C6BgTyjpWs+IiIigDHyEDmIRNiEeYRPiETYhHmELYtEul66kmh3ivlt/xK/H1SpTSO6vHy8Xk1Pkvnpl5d3Fu6Vk4bzypwblpHB0lAQLR5DHoz85jdw37KpgPQ36VatWhU0DMdiLWIRNiEfYhHiETYhH2IJYtIsuc3u7a13TmDsjQ+6pKv96vJnHsY2HfpcXZm+SV37YJg1HL5APf9ojo+dslUaj58tv+zyX0wXC1Qx21AvneKSHEgAAAAAAyDZamfPa/XXMEri7qhWXW8sWlmm/HZR65eOkQ+1Skju375U7l65clS4Tlkv7W0vJ6/fXMQmrtImen3edMjvSxWeSxEorKTlVNh85J1ERueWzX/ZJbEwe6de8shTJnyddE3Fn36exXWpLyxolJC4mj0T4MYdQRUIJAAAAAABkq4YVi5ibU60yhdON+Wvb6jJm7lafzvf9+iPm1r9FZXmmTXVz7Mi5JOnwj2Vy6mKy+TwmT4RM73+H1CiVfqnWz7tOysw1h0zySRNCGw6dSzdGd5+b0ruRTFi8S+ZsOCLHfr/scf8z0zeIyAa5uXgB+XZgE4nO45ncCjcklAAAAAAAwA33WNNKUr98nJQrGiPFCuSVs4lX5Nj5S+a+6iULyW/7zkiXCT97PGbCol3m1rZWSZm78ajHfYnJqdJ23FLz71fvu1UaVCgiT3y1VpJTr5oldU4HzyR5vZ6dxy+Y5XbXouMe/nCFTHmssalwClc05c5mNOUGrh+xCJsQj7AJ8QibEI+wBbEY2vacvCh3vbYoR5+jWdVismT7Cb8f99K9teShxuVDKh79yWlQoQQPycnJZntDINCIRdiEeIRNiEfYhHiELYjF0FXxpvyyZ0w7U73U99Pf5Ne92dOg+y933yxF8+eR9reWloL5IuWOlxfK6f8snXOnvZIWDm0uxQvmkx3Hz8ua/WdN83A1fNZGKVU4n+mrFI7xSIVSNgvmCqWUlBTTjT4hIUEiI8k1InCIRdiEeIRNiEfYhHiELYjF8LL92Hn503vL5UziFfN5sYJ5Zeaf75QysdGSmJwiX/x6QP7+3Wavjx3dubZ0a1TO6326k9wb87bL6n1n5eE7ysuzbapnWGHU++OVMn/LcfPvuJgoWfncPRL5n6VvwR6PVCgBAAAAAICQU7VEQfnxyRYmoaRJJN1szZnMickTKb2aVJQ6ZQtL/89Xy7mkK9K+dilTgaRNwR9IiM/wvPXLF5HPezc2S9autVRtfPd6cvdri+XQ2SRzHa3eXCJzBjUNuybdJJQAAAAAAEDQiI3JY24ZSahQxFQN+ZIcSsuX8XkjI+TZttXlL1+scfV5qjHiB9OLadJDdSVchG87cniljcMAGxCLsAnxCJsQj7AJ8QhbEIvwJiebYv+xTmkZeNfNHse0sXerccvCJh7poZTNgrmHEgAAAAAA8N136w/LwCn/X6nkNO7B26TTbWUk1HMaVCjBRXOLZ8+eNR+BQCIWYRPiETYhHmET4hG2IBYRSB1uLS1f97vd49js1QfCIh5JKMElNTVVtm7daj4CgUQswibEI2xCPMImxCNsQSwi0BpUKCLLnrlLHmtaUV78Yw3pVcMRFvFIU24AAAAAAIDrUDYuRp5rX1NSUlJk1arjEg6oUAIAAAAAAIBfSCjBowN+dHR0jnbCB3xBLMImxCNsQjzCJsQjbEEswia5wige2eUtm7HLGwAAAAAACEYhv8tbYmKi1K9fXx555JEMx2iebMKECVKrVi2THaxRo4ZMmTIlw/FTp06VhIQEyZ8/v1SsWFHeeustCTdXr16V48ePm49AIBGLsAnxCJsQj7AJ8QhbEIuwydUwisegSyjpN+Whhx6S1atXZzruz3/+swwYMMBk1/r16yfx8fHSvXt3+eSTT9KNfeWVV+TBBx+UvXv3Ss+ePU2yasiQIfL3v/9dwol+bXfv3h0WgQ+7EYuwCfEImxCPsAnxCFsQi7DJ1TCKx6Da5e3s2bPStWtX+eGHHzIdN3fuXFOdVK1aNVm+fLnExcWZ4926dZNBgwZJ27ZtpVixYubYxo0bZdiwYebzlStXSvny5c3xv/71rzJy5Ejp0qWL1KxZ8wbMDgAAAAAAIDgEVYVSw4YNZcmSJTJu3LhMx/3zn/90VR45k0nqhRdeMOsAp0+f7jqmiafU1FR5/vnnXckk9fTTT0uePHm8VjQBAAAAAACEs6BKKGljqF9//VU6duyY6bjFixdLTEyMqURypxVLmjSaN2+ex1illUjuNBHVoEEDj7GhTrvQ69c4HLrRw27EImxCPMImxCNsQjzCFsQibJIrjOIxqBJKv/zyi9xyyy2ZjtGeSRcvXjTNuKOiotLdX6VKFdm1a5fr88OHD0vx4sWlTJkyXsfq2sdwERERYZqX60cgkIhF2IR4hE2IR9iEeIQtiEXYJCKM4jGgPZS++eabazbXVr169TI7r/nyDdGEkipRooTX+7XyaO3atR7jM+qRpGO1b5MmqHT3t1CnTcM0wVa6dGnJnTuoco0IMcQibEI8wibEI2xCPMIWxCJscjWM4jGgCaXZs2fLxx9/fM1x99xzj0ko+cKZdNIlb97kzZtXEhMTPcZnNlbp+IwSSpcvXza3tAmtlJQUc1MaRHrTwHLv9O48rj2cHA7HNY/rtWrZnPO8aees4305HhkZac7rflzPq8cOHDhgGpQ7H6vH9d8ZXbvtc/J27czJ/jnp/RqLJUuWNJ+HwpwyO86c7J6TMx61mlV764XCnNJeI3MKnjlduXLF9btaK7FDYU6h+H0Klzm5x6M+PhTmFIrfp3CYk445ePCgx/uYYJ9TKH6fwmVOqW7vZdLu9BYMc/Jnd7qAJpQmT55sbtmpQIEC5qN7ksddcnKyubmPz2ys+0dvxowZIy+++GK642vWrHElofQHW+XKlWXPnj1y4sQJ15iyZcua2/bt202zcKdKlSqZNy66A11SUpLrePXq1SU2Ntac2z2gbr31VvMmZ9WqVR7XkJCQYK59/fr1rmMaYNobSp9v69atruPR0dFmOaGO16ox53pPXfup5XqaYdUf0k7BMqc6derIyZMnPZYuMif756Q/0LQyUIXKnELx+xQuc9J41GrVffv2maXQoTCnUPw+hcucjh8/buJRf1fHx8eHxJxC8fsULnPauXOnKx71tWMozCkUv0/hMCfn5kqbN2/2eG8XzHMKxe9TuMzJ4XC4kmPBOCcd76tcDvdUVJDYu3evqVjq0aOH14SUfiErVKgg69atS3dfixYtzA8afUGm9BuhbxL0l2FajzzyiKmg0je2GVUxeatQ0hd4p06dkkKFCgVV5laPrVy5UurVq0eFEnMKeIWSvjjVH6DO6w/2OWV2nDnZPSdnPNavX58KJeYU8DlpRYjGo/6upkKJOQV6Tvoa2BmPVCgxp0DOScdoLNatW5cKJeYU8Dmlur2XSSsY5nThwgXT/keTTM6chpUVSjlFf5AsX75czp8/LwULFnQd1wDVTKBm59zHahZw27ZtZhc4d3oO/QJmlExyLotzLo1L+43XmzvnNywt9x96vhxPe96sHNdgS3tcg0uzq84XqL5cu+1zysq1M6fAz0k/aiw6j4XCnK7nOHMK7Jyc8eh8bCjMydfjzMm+Oenv6LS/q4N9TqH4fQqXOXmLx2CfUyh+n8JhTvo+xn0p8PVce0bH+T4xp8yuPcLteNr3Mr5euy1zyuiavQnJDlGdO3c25WITJ070OP7111+baiPtyeQ+Vo0fPz5dMklLv9zHhjoNHE22+RNAQE4gFmET4hE2IR5hE+IRtiAWYZPcYRSPITnDRx991OzyNnz4cJk1a5YrQTR06FCT2dOlck4dOnQwvYM0ofT++++b7LauT+zZs6drh7lwoXPftWuXX024gJxALMImxCNsQjzCJsQjbEEswiZXwygeQzKhpMvUtBopX758cu+995rm2HfccYccPXpUXn75ZdMIy728a9q0aVKmTBnp27evadJds2ZNk1QaNGiQtGvXLqBzuZE04LVJVzgEPuxGLMImxCNsQjzCJsQjbEEswiZXwygeQ7KHkmratKls2rRJXnnlFdM3SdcwDh482BxPS7vKa1f21157TZYsWWL6LvXu3Vs6deoUkGsHAAAAAACwWVAmlHQHN182pytZsqS88cYbPlc1jRw58rqvzXlduttbsNGm5dpjSq89oyZhwI1ALMImxCNsQjzCJsQjbEEswiYpQR6PzlyGLzmX4Jud5XRnORUfHx/oSwEAAAAAAMhSbqNw4cKZjsnl8CXtBJ/pOsnDhw+bZXO6vV+wZSI1EXbgwAFTsQUECrEImxCPsAnxCJsQj7AFsQib/B7k8agpIk0mlS5d+po71VGhlM30C162bFkJZhr0wRj4CD3EImxCPMImxCNsQjzCFsQibFIoiOPxWpVJIb3LGwAAAAAAAHIOCSUAAAAAAAD4hYQSXPLmzSsvvPCC+QgEErEImxCPsAnxCJsQj7AFsQib5A2jeKQpNwAAAAAAAPxChRIAAAAAAAD8QkIJAAAAAAAAfiGhBAAAAAAAAL+QUApyO3bskPvuu0+KFy8uUVFRctNNN0nfvn3l3LlzHuMuX74so0aNkqpVq0p0dLTUq1dP5s2bl+m5U1NTpX379tKiRYtMx02dOlUSEhIkf/78UrFiRXnrrbeyZW4IPoGOR32eoUOHSoUKFSQyMlIKFChgHrNly5ZsmyOCR6DjMS1tWdiyZUsTnwgvNsXiiRMnpFixYlKqVCk5e/bsdc0LwSnQ8ahx169fP7n55pvNeePj46Vr167muhB+ciIejxw5Ij179pQyZcqY14OFCxeWBx98UA4dOuT1d/OECROkVq1a5rw1atSQKVOm5Nh8YbdAx+MRP8ZaQ5tyIzht3rzZUbhwYW2q7qhUqZKjTZs2jqJFi5rPGzdu7EhJSTHj9GOHDh3M8Ro1ajiGDh3qaNSokSMiIsKxcOHCDM8/aNAg85jmzZtnOGbs2LFmjD7vwIEDHV26dDGfjxw5MkfmDHsFOh4TExMdt912myseW7du7ahcubL5PC4uznHgwIEcmzvsE+h49Obtt982jylfvny2zBHBwbZYvP/++834r776KtvmiOAR6HhMTk52JCQkOKKiohzdunUz523fvr05b2xsrLk+hI+ciMdjx4454uPjzdjSpUubc5YpU8b1HOfPn/cY379/f3OfPubxxx93tGrVynz+8ccf39CvBQIv0PF4zM/YtQUJpSDWrFkzE7gTJ050XL161Rw7c+aMo1atWibwZsyYYY6988475vOmTZs6Ll265PofoUmTJuaNjf5yd6djevToYR6T2YuCDRs2mOcvVqyYY+/eva7jzz77rCMyMtKxadOmHJw9bBPoeBwxYoS5v2/fvia5pFJTUx0PP/ywOT548OAc/grAJoGOx7R27NjhiImJIaEUhmyKxWnTppmx+kIY4SnQ8fjBBx+Y+6dOnepx/MsvvzTH9RwIHzkRj87XfS+++KLjypUr5pg+pmXLlub4m2++6Ro7Z84cc6xatWqO06dPu4537drVJBaOHz9+w74WCLxAx+PDfoy1CQmlIM6gatLmqaeeSnefM8iHDRtmPq9Zs6b5fO3atR7j/vWvf5njc+fO9TiumXn9n+ndd9/N9EXBgAEDzP3jxo3zOK4/kPWN0zPPPJMNM0UwCHQ86g/xcuXKORo2bOj12vRxd9xxRzbMFMEg0PGYliY29UWGXpP+xYmEUviwKRZPnjzpKF68uCN//vyOffv2Zcv8EFxsiMd+/fqZ+y9cuOBxXP/yrsdvv/32bJgpwjUe9c1/gQIFTCVmWs7kkVbGObVr184cmzVrlsfYrVu3muMTJkzItvnCboGOxzN+xq5NIgO95A5Zo+t7ExMT5erVq+nuS0lJMR8jIiJMr4TNmzebdep16tTxGKfr2/PkyWPWe7Zp08bjvkWLFkmTJk3MGveMLF682Hzs0qWLx/G4uDhp0KCBOe/LL798XfNEcAh0POq59+7da64hs+dHeAh0PKb1xhtvyLJly2TkyJGyYMECE6sIDzbF4sCBA+X48eMmHsuVK3fdc0PwsSEetd+m0vPra0WnDRs2mI/0mAsfORGPsbGxpkdXcnJypud0fy8TExMjbdu29RhbrVo1KV++vDmvr7/rEdwCHY+xfsauTUgoBTFtFObNt99+az7eeeedprGX0kZhaWnA64vKXbt2eRyfO3euTwF7+PBh07BMm4alVaVKFZk2bZrPc0HwC3Q85sqVy/VCNaPnR/gIdDw6aUP44cOHS6NGjWTYsGEmoYTwYkMs6nN9+eWXprnnhQsXZMiQIeZ3d7du3aR06dJZmBWCVaDj8f777zebt/Tu3Vs++ugjqV69ukkmPfbYY5I7d27p06dPFmeGYJQT8ahxqE2SMzun+v333+XixYvSsGFDr9eh72XSxjlCWyDj0d+xNmGXtxCzfPlykxXVLGurVq3MD0tVokQJr+O1miht13hfX6DquTM7r2ZZ9Qc1wteNjEdvdEeGcePGmR/w/fv3z/J5EBpudDzqbkc9evQwb5I+/fRTa/+yhNCORd2JZvDgwa6fiSNGjDBv6J966inz/PzxBzcyHjW5/vXXX5tke/369c0fgho3bmz+6j9z5ky/ds5EaMqOeExrz5495vew7tjVvXt3cyw7zovQd6PiMTvGBgoJpRBy6dIl8xcepW+i9U2M8xe8lnN6kzdvXq/LhHyh587svCqr50bwu9Hx6M0TTzxhlnjoGyeWeIS3QMSjLvlduXKlvPbaa+YvnUAgYnHSpEnmBalWcb744ouydetW82b+pZdeMskmfYG6adOm65gRgtmNjketkNOE5pUrV8zzlCxZ0myNrQml999/X06dOnUds0Gwy4l41J7BWvmm5x4zZowUKFDAHL/Rr0kRfG5kPF7v2EAioRRC9M2zvigcMGCAyaAqZ+Dpi0ZvdJ2mt7WavtBzZ3Ze948IPzc6HtP66quv5MMPP5S6deuav8gjvN3oeFy/fr3pmaRr6KmOQyBjcfr06ebj448/bn4Wam8QXWb03HPPyahRo8x5P/jggyzPB8HtRsfj0KFDZcmSJeb5Tp8+bZaP6E2XwH333XdmSRzCV07E46uvvirz58+X9u3bmzhzupGvSRGcbmQ8Xu/YgAp0V3Bkj08++cR0f09ISHBtX+jccU2Pd+zY0evjdLehBg0aZHjezHbquPXWW82Wmt44t469ePGi33NB8AtEPLrbtGmTo2DBgo7Y2FjHzp07szgLhIobHY+6XWydOnUcRYsWdRw+fNjjPh3PLm/hKxA/G6tUqWLu37BhQ7r79Jje17Zt2yzNB8HtRsejboMdHR1tXj86t+R217hxY/PY/fv3Z3lOCF45EY8LFy40O3dVqFDBcerUqXT3FypUyMSjNxrDxYoVy/J8ENwCEY9ZHRtoVCiFgBUrVphyOG2Q/c0337iWmznXceouBatWrTJlc+70L0L79u2TUqVKZel5tfJD+zFs27bN63rTQoUKZVgOiNAVqHh00nL5Tp06mf5dU6ZMkcqVK1/X+RDcAhGPumxj3bp1Zr39+PHj5fnnn3fddOmR9pfTf7/++uvZMkcEh0D9bNTfxcrbz0JddqS0zxzCSyDi8eTJk5KUlCQ1a9Y0SzDTqlWrlvl48ODBLM0JwSsn4lEbIz/wwAPm55ues0iRIl7fy+gy4PPnz6fbVUuf73pfkyI4BSoeszLWBiSUgpwmc/74xz+aLQ414OLj49ON6dy5s9mRbcaMGR7HJ0+ebD7ec889WXpuPa/SN0xpk0nbt2/P8nkRvAIZj0qTSB06dJCdO3fK2LFj020Di/ASqHjUXiBq2bJlZkmR+23//v0mEa//fvvtt7M8NwSXQP5s1DdMSmMvLU18qrRbHyO0BSoetams9h/R39HeaM855ziEj5yIx2PHjpkl5/pHRh3j/Dno7by6PGnixIkex7VxvL6m5L1M+AlkPPo71hqBLpFC1u3atctRsmRJU3b36aefZjouJibGlG0uW7bMHJs9e7ZZEqSlnkeOHMlSGX1KSorjlltuceTOndvx3nvvOVJTUx1btmxxVK9e3Tzu+++/z4ZZIlgEOh6TkpIczZo1M2N69+6dDTNCMAt0PGaEJW/hJ9Cx+OOPP5r7/+d//scsx3TS5ZhaSq+/w7du3Xpdc0TwCHQ81q5d29z/zjvvmCVw6ty5c46nnnrKHK9atep1zxHhHY8nT5501KhRw5zzpZdeyvT5NfZKlChhzj1z5kxz7Oeff3aUKlXKLDdat25dts0V9gt0PJ70Y6xNcul/Ap3UQta0bt3abGNYqVIl6dq1a7r7K1asKL169XJl2nX7ai011mVo2n0+KipKPvvsM1NSlxEtSW7evLksWrTI6/1aJqrXceDAAYmOjjZd6DWkBg0aZLrhI3wEOh5Hjx5tmszmy5fPbJGtu8akpbsaITwEOh4zolti792719wQHmyIRW0oOmHCBNOMu2XLlmZ5x+zZs83yy+HDh5sG8ggPgY7HuXPnSseOHc2SIn3dqEsytapTqwG0eknvdza/RejLiXjUpUpacVS0aFHp169funPqkiVtDu+0dOlSuffee02TeOd5NYa1IbL7OIS+QMdjHz9j1xqBzmgh66KiokwGM6Nb2r8O7dixw9GnTx9HkyZNHN27d3esX7/+ms/hy1/gNbs/fPhwM65Dhw6uDD/CS6DjsVWrVpk+Pz/uwkug4zEjVCiFH1ti8YsvvnDcfffd5i+q+pdVbUQ7adKk654fgosN8bhixQpH586dHcWLFzdVIHFxcY7WrVs7Fi9enC1zRHjHo3Mjgoxu3n4Ha0XJkCFDHE2bNnV06dLFsWTJkhydN+wU6HiskoXYtQEVSgAAAAAAAPALTbkBAAAAAADgFxJKAAAAAAAA8AsJJQAAAAAAAPiFhBIAAAAAAAD8QkIJAAAAAAAAfiGhBAAAAAAAAL+QUAIAAAAAAIBfSCgBAAB4ceXKlUBfAgAAgLUiA30BAAAAgTJjxgwZMmSIbNu2TfLmzes6Pn/+fOnRo4f89NNPUqFCBbl8+bKkpqZKnjx5JDIye18+JScny88//ywtWrTIdNypU6ekU6dO0qxZMxk9erRP505JSZELFy74NDY2Ntbr8SNHjsi5c+d8OkeVKlUkIiLC49i///1vad26tU+PBwAAwSOXw+FwBPoiAAAAssvRo0fl0qVLHscKFSokRYoUSTd26tSp8uCDD5pkUe7c/y3cTkpKkjvvvFOioqJk2bJlMnbsWBk+fHiGz6mJnpkzZ/p9rXqdXbp0MR8XLFhwzfF16tSRw4cPy6FDh0xy61rmzZvnczJHr8E9qebUs2dP+eijj3w6x/Hjx6VYsWKuzw8ePCj16tWTJ554Qp599lmfzgEAAIIDS94AAEBI6datm1SsWNHjNnLkSK9jtdooV65cHsmk06dPy9WrV2Xy5MlSuXJlU6EzYMAA2b17t0nknDhxwuPWuXNnn5I73miyRp//u+++8ziuVUWa5Epr8ODBpkJJnzetxMREU0nlLl++fOaj/v0wo9uPP/5orsFbMklpxVH9+vUzPceECRNcX093ZcuWNVVeer9+PQEAQOhgyRsAAAgpmtTo1auXTJo0yXzeuHFjc2zdunUm4aJVR5ok0SSSVtBoMmXt2rUmIdOoUSOTPLnvvvvk1VdflSlTprjO663CSWV1Gdxnn30mq1atktWrV0t0dLTHfR06dJAlS5ZkmKj6/vvv0y1t0wTUF198YSqunHRuSpftZVaZ5J5QS8ufuaVd7uZcBjd9+nT5wx/+IE2aNJGbb77Z5/MBAAB7kVACAAAhRRNG3pIiAwcOlDVr1riSSXrTxttajaT9izSxcuzYMbM8zpng0f5GmmjyRsdllojJjD7niBEj5MMPP5QCBQqku//rr782lT+aUNKkkyaQnn/+eY+EjS5n0+ofPY+eT/sc3XTTTR7ncVY57d27N8NrWbRokbRs2dKvJJG/YxMSEqRPnz5m6eDEiRN9Ph8AALAXS94AAEBI8Zbk0WNLly41S8k08XLmzBnT5PqTTz4xSZCzZ8+ahFLhwoVNQsp5jmnTpklcXJzXmzbyzirtl6TL0TJqxK19iIoXL26Wtv3v//6vqZQ6efKkaZztvGlV1T/+8Q+zxE+TT7o8T6/fnfaCcibUMrppMkkTUhntauescvJFZmP79u0rX375peuaAABAcCOhBAAAQoomNT744APzUW8rVqxwJTo0oaRNu32llUpFixb16Bd04MABj/5EWbF+/Xqz/Cszy5cvN2MKFixodoGrVq2ax/3a5FqXkv36669y2223mUqjtNq0aWOuWauzNFGmDb11eZz7TauYdIy3yi6lXzut1NIqp4xumpxzjs2ILrvTZYM7d+708asEAABsRkIJAACEFK0u+tOf/iR79uwxN022OBMdWo3z5JNP+nwufZwmW7SCyXn7/fffXfdllTb6LlGiRIb3z5o1S5o2bWqqjr755hsZMmSI7Nq1y2PMqFGj5G9/+5upvIqJiZHt27d7PdfHH39sKpn0HFr15C+d54YNG9I1One/6XI859jMlCpVyiS1AABA8COhBAAAQoou39K+RFoRozf33cv+8pe/mGVX/lTJ6K5v7kvdbrnlluu+Rq180iVsGenUqZO8++67snDhQqlatarp/TRmzBjX/frY8ePHm0bXej0bN240PYrcaSJs9OjR8uijj5pEzyuvvGKSbfpv53K3tP/etGlTumvR477u8nYtet2a/AIAAMGPhBIAAAgpzkbU7jTpoXQHNF125Z6cuZaMlrxdjxo1aphlb5np3bu3WVanjbmfe+45mTx5stmpTq/hsccek7Jly8rIkSPNWPekmdJqJu3P9MILL5ilcdpYXJem6WN0OaAudXvmmWfMjmva00iX1DkriDL62vkis7Fa2bV//36pXr26z+cDAAD2Ypc3AAAQchVK2ivJubPZ5cuXzTGllTjjxo2TevXqXXeCxJ9ES1qtWrUylUObN2+WmjVrXnO8Vh9pZdVDDz0kHTp0kPnz58svv/ySYR+n+Ph4ad68ualy0uTVsmXL5JFHHpFevXpJz549TWLq9ddfNz2YtHeSJqC0qkuTbdcjs6+JJsTq1q1rGo4DAIDgR0IJAACEXIXS1KlTzc3pnnvucf27a9euPp9Ld37ThtPeegPpfVmlSRXdve2JJ56QuXPnXrP3kC5Ve++990zySZe3TZo0KdOld1rVpNVL2pBc+0lpBdJbb70lXbp0MX2l2rVrZ6qc2rdvb8ZrQkl7IXnjTMZdT0Lp2LFjpipMk3kAACA0sOQNAACEXEJJK3GcS9SaNWvm9+OdiRFNwJw5c8brzbnrWlYrlTTBosvedFnatWhFUseOHc2SNE0qDRs2TCZOnGiWq2VEK5j69u0rDRo0MJVQOpfvv//efK4JNvfkjvaUqlSpUoZfj99++821a563W//+/V1j09Jr1CSe9mF64IEHfPzqAAAA21GhBAAAQor2PHJfurV48eJMG26nrQ7S5XLJycmuSh+9ebN161aTqFm+fLlpjp2VKqVvv/3WJHfOnz8vb775pus+Xaan5543b56ptNIlapokGzt2rOmXNGLECBk0aJA8/fTT5rl1eZsmmurUqSOxsbHmHI0bN5a1a9ea+cyZM8c0zt69e7d5Hq2O0qTYokWL5NChQzJt2rQMd7/TJFHt2rVl9uzZGc7l888/Nzu9aW+mtH2T2rRpY76eM2bM8PtrBAAA7EVCCQAAhJSvvvrqmmNWr15tdlI7ceKE6evj7uLFi66EUmb27dtnqn60X9HDDz+cpWvVqh3tb6TVRE6alNHE0LZt26RQoUKmuueLL74wu705vfrqq/L444/L+++/b5I5mnTSRNOWLVtcCSWl89Pm3GXKlDFJpO7du7saeBcuXFhGjRolV65cMX2VhgwZ4vUa9X5NqumOeZkl8ZzX7i5//vxmed3gwYOlYMGCWfoaAQAAO+VyXE9HSQAAgCClTanLlStnKmiykuzQHkpHjx7NNNGSVQsXLjRVSpoMio6OvuZ47YGkvZHce0U56Uu9a/VoAgAA8BcJJQAAAAAAAPiFptwAAAAAAADwCwklAAAAAAAA+IWEEgAAAAAAAPxCQgkAAAAAAAB+IaEEAAAAAAAAv5BQAgAAAAAAgF9IKAEAAAAAAMAvJJQAAAAAAAAg/vg/gYEM7PefPL4AAAAASUVORK5CYII=",
      "text/plain": [
       "<Figure size 1200x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#因子_ZScore\n",
    "plot_cumulative_sum_ic(ic_zscore, '因子_ZScore')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "id": "0d84be5f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 1200x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#因子_ZScore\n",
    "plot_cumulative_sum_ic(ic_neutralized, '中性化因子_两步法')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d81401f1",
   "metadata": {},
   "source": [
    "### **2.分层回测图**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "id": "8737aa8a",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "分层回测进度: 100%|██████████| 2909/2909 [00:06<00:00, 446.46it/s]\n",
      "分层回测进度: 100%|██████████| 2909/2909 [01:42<00:00, 28.25it/s]\n",
      "分层回测进度: 100%|██████████| 2909/2909 [00:06<00:00, 436.27it/s]\n"
     ]
    }
   ],
   "source": [
    "# 1.分层回测核心函数\n",
    "# ----------------------\n",
    "def stratification_backtest(\n",
    "    data, \n",
    "    factor_column, \n",
    "    return_column, \n",
    "    market_cap_column='市值', \n",
    "    industry_column='LEVEL1_NAME', \n",
    "    n_layers=5, \n",
    "    weighted_type='equal', \n",
    "    neutralize_industry=False\n",
    "):\n",
    "    \"\"\"\n",
    "    分层回测主函数：支持全市场分层、行业内分层，等权/市值加权，添加进度跟踪\n",
    "    :param data: 原始数据（含因子、收益率、市值、行业）\n",
    "    :param factor_column: 因子列名（如 '因子_ZScore'）\n",
    "    :param return_column: 收益率列名（如 '收益率'）\n",
    "    :param market_cap_column: 市值列名（默认 '市值'）\n",
    "    :param industry_column: 行业列名（默认 'LEVEL1_NAME'）\n",
    "    :param n_layers: 分层数（默认 5 层）\n",
    "    :param weighted_type: 加权方式 'equal'（等权）/ 'market_cap'（市值加权）\n",
    "    :param neutralize_industry: 是否行业内分层（默认 False：全市场分层）\n",
    "    :return: 各层累计收益率（DataFrame）、分层收益表（DataFrame）\n",
    "    \"\"\"\n",
    "    # 按日期分组处理，用tqdm包裹迭代器显示进度\n",
    "    date_groups = list(data.groupby('DATE'))  # 先转成列表，方便获取长度\n",
    "    backtest_results = []\n",
    "    # tqdm参数说明：total是总迭代次数，desc是进度条描述\n",
    "    for date, group in tqdm(date_groups, total=len(date_groups), desc=\"分层回测进度\"):  \n",
    "        # 过滤缺失值\n",
    "        group_clean = group[[factor_column, return_column, market_cap_column, industry_column]].dropna()\n",
    "        if len(group_clean) < n_layers:\n",
    "            continue  # 样本量不足，跳过该截面\n",
    "        \n",
    "        # 分层逻辑：全市场 / 行业内\n",
    "        if neutralize_industry:\n",
    "            # 行业内分层：按行业分组后，每组内部分层\n",
    "            layer_returns = []\n",
    "            for industry, ind_group in group_clean.groupby(industry_column):\n",
    "                if len(ind_group) < 2:\n",
    "                    continue\n",
    "                # 行业内因子排序\n",
    "                ind_group['rank'] = ind_group[factor_column].rank(pct=True, method='first')\n",
    "                ind_group['layer'] = pd.qcut(ind_group['rank'], q=n_layers, labels=range(1, n_layers+1))\n",
    "                # 计算行业内各层收益\n",
    "                for layer, sub_group in ind_group.groupby('layer'):\n",
    "                    if weighted_type == 'equal':\n",
    "                        ret = sub_group[return_column].mean()\n",
    "                    else:  # 市值加权\n",
    "                        weights = sub_group[market_cap_column] / sub_group[market_cap_column].sum()\n",
    "                        ret = (sub_group[return_column] * weights).sum()\n",
    "                    layer_returns.append({\n",
    "                        'DATE': date,\n",
    "                        'layer': layer,\n",
    "                        'return': ret,\n",
    "                        'industry': industry\n",
    "                    })\n",
    "            # 合并行业内分层收益（按层等权/市值加权汇总）\n",
    "            layer_df = pd.DataFrame(layer_returns)\n",
    "            if weighted_type == 'equal':\n",
    "                layer_ret_summary = layer_df.groupby('layer')['return'].mean().reset_index()\n",
    "            else:\n",
    "                # 市值加权需用全市场市值计算行业权重\n",
    "                total_mktcap = group_clean[market_cap_column].sum()\n",
    "                industry_weights = group_clean.groupby(industry_column)[market_cap_column].sum() / total_mktcap\n",
    "                layer_df = layer_df.merge(industry_weights.rename('industry_weight'), left_on='industry', right_index=True)\n",
    "                layer_df['weighted_return'] = layer_df['return'] * layer_df['industry_weight']\n",
    "                layer_ret_summary = layer_df.groupby('layer')['weighted_return'].sum().reset_index()\n",
    "        else:\n",
    "            # 全市场分层：直接按因子排序\n",
    "            group_clean['rank'] = group_clean[factor_column].rank(pct=True, method='first')\n",
    "            group_clean['layer'] = pd.qcut(group_clean['rank'], q=n_layers, labels=range(1, n_layers+1))\n",
    "            # 计算各层收益\n",
    "            layer_ret_summary = []\n",
    "            for layer, sub_group in group_clean.groupby('layer'):\n",
    "                if weighted_type == 'equal':\n",
    "                    ret = sub_group[return_column].mean()\n",
    "                else:  # 市值加权\n",
    "                    weights = sub_group[market_cap_column] / sub_group[market_cap_column].sum()\n",
    "                    ret = (sub_group[return_column] * weights).sum()\n",
    "                layer_ret_summary.append({'layer': layer, 'return': ret})\n",
    "            layer_ret_summary = pd.DataFrame(layer_ret_summary)\n",
    "        \n",
    "        # 保存每日分层收益\n",
    "        layer_ret_summary['DATE'] = date\n",
    "        backtest_results.append(layer_ret_summary)\n",
    "    \n",
    "    # 合并结果并计算累计收益\n",
    "    backtest_df = pd.concat(backtest_results, ignore_index=True)\n",
    "    backtest_df = backtest_df.pivot(index='DATE', columns='layer', values='return')\n",
    "    \n",
    "    # 计算累计收益（等权/市值加权通用逻辑）\n",
    "    cumulative_ret = (1 + backtest_df).cumprod() - 1\n",
    "    return cumulative_ret, backtest_df\n",
    "# ----------------------\n",
    "# 2.执行分层回测（全市场 + 行业内，两种因子）\n",
    "# ----------------------\n",
    "# 2.1. 因子_ZScore 全市场分层（等权）\n",
    "cumulative_zscore, daily_zscore = stratification_backtest(\n",
    "    data, \n",
    "    factor_column='因子_ZScore', \n",
    "    return_column='收益率', \n",
    "    weighted_type='equal', \n",
    "    neutralize_industry=False\n",
    ")\n",
    "\n",
    "# 2.2. 因子_ZScore 行业内分层（等权）\n",
    "cumulative_zscore_ind, daily_zscore_ind = stratification_backtest(\n",
    "    data, \n",
    "    factor_column='因子_ZScore', \n",
    "    return_column='收益率', \n",
    "    weighted_type='equal', \n",
    "    neutralize_industry=True\n",
    ")\n",
    "\n",
    "# 2.3. 中性化因子_两步法 全市场分层（等权）\n",
    "cumulative_neutral, daily_neutral = stratification_backtest(\n",
    "    data, \n",
    "    factor_column='中性化因子_两步法', \n",
    "    return_column='收益率', \n",
    "    weighted_type='equal', \n",
    "    neutralize_industry=False\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 68,
   "id": "cf6a3083",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1200x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1200x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1200x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 3.可视化分层收益曲线（对应第十步需求）\n",
    "# ----------------------\n",
    "def plot_stratification(cumulative_ret, title):\n",
    "    \"\"\"\n",
    "    绘制分层回测累计收益曲线\n",
    "    :param cumulative_ret: 各层累计收益率（DataFrame，索引为日期，列为分层）\n",
    "    :param title: 图表标题\n",
    "    \"\"\"\n",
    "    plt.figure(figsize=(12, 6))\n",
    "    for layer in cumulative_ret.columns:\n",
    "        plt.plot(cumulative_ret.index, cumulative_ret[layer], label=f'Layer {layer}')\n",
    "    plt.title(title)\n",
    "    plt.xlabel('Date')\n",
    "    plt.ylabel('Cumulative Return')\n",
    "    plt.legend()\n",
    "    plt.grid(True)\n",
    "    plt.show()\n",
    "\n",
    "# 4.绘制曲线\n",
    "plot_stratification(cumulative_zscore, '因子_ZScore 全市场分层（等权）累计收益')\n",
    "plot_stratification(cumulative_zscore_ind, '因子_ZScore 行业内分层（等权）累计收益')\n",
    "plot_stratification(cumulative_neutral, '中性化因子_两步法 全市场分层（等权）累计收益')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 69,
   "id": "9fec7dbf",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "因子_ZScore 分层单调性（Spearman）：-0.7000，Top-Bottom 收益差：-0.0007\n",
      "中性化因子_两步法 分层单调性（Spearman）：-0.7000，Top-Bottom 收益差：-0.0007\n"
     ]
    }
   ],
   "source": [
    "# 5.评价指标计算（单调性、收益差等）\n",
    "# ----------------------\n",
    "def evaluate_stratification(daily_ret, n_layers=5):\n",
    "    \"\"\"\n",
    "    计算分层回测评价指标：单调性、Top-Bottom 收益差\n",
    "    :param daily_ret: 每日分层收益（DataFrame，列为分层）\n",
    "    :param n_layers: 分层数\n",
    "    :return: 单调性（Spearman 相关系数）、Top-Bottom 收益差（均值）\n",
    "    \"\"\"\n",
    "    # 单调性：分层与收益的秩相关\n",
    "    layer_order = np.arange(1, n_layers+1)\n",
    "    corr, _ = spearmanr(layer_order, daily_ret.mean())\n",
    "    \n",
    "    # Top-Bottom 收益差\n",
    "    top_bottom_diff = daily_ret[n_layers].mean() - daily_ret[1].mean()\n",
    "    return corr, top_bottom_diff\n",
    "\n",
    "# 计算评价指标\n",
    "corr_zscore, diff_zscore = evaluate_stratification(daily_zscore)\n",
    "corr_neutral, diff_neutral = evaluate_stratification(daily_neutral)\n",
    "\n",
    "print(f\"因子_ZScore 分层单调性（Spearman）：{corr_zscore:.4f}，Top-Bottom 收益差：{diff_zscore:.4f}\")\n",
    "print(f\"中性化因子_两步法 分层单调性（Spearman）：{corr_neutral:.4f}，Top-Bottom 收益差：{diff_neutral:.4f}\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8638c489",
   "metadata": {},
   "source": [
    "## **十一、通过二次规划对因子值最小的100个股票进行个股上下限和行业约束**"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b6719643",
   "metadata": {},
   "source": [
    "### **1.ZScore因子**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 81,
   "id": "0b7c89b9",
   "metadata": {},
   "outputs": [],
   "source": [
    "# 1. 筛选因子值最小的100只股票\n",
    "n_stocks = 100\n",
    "selected_stocks = data.sort_values('因子_ZScore', ascending=False).head(n_stocks)  # 升序排序，最小为1%分位\n",
    "n = n_stocks"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 82,
   "id": "a71f4b54",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "100"
      ]
     },
     "execution_count": 82,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(selected_stocks)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 83,
   "id": "5f522799",
   "metadata": {},
   "outputs": [],
   "source": [
    "# 2.无行业基准权重，采用行业等权约束（替代方案）\n",
    "selected_stocks['行业权重'] = 1 / selected_stocks['LEVEL1_NAME'].nunique()  # 各行业等权分配"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 85,
   "id": "af6ca655",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "np.float64(0.09598661379469095)"
      ]
     },
     "execution_count": 85,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 3.求解模型\n",
    "\n",
    "# 定义变量\n",
    "w = cp.Variable(n)\n",
    "\n",
    "# 目标：最大化预测收益\n",
    "objective = cp.Maximize(selected_stocks['收益率'].values @ w)\n",
    "\n",
    "# 约束条件\n",
    "constraints = [\n",
    "    cp.sum(w) == 1,                # 权重和为1\n",
    "    w >= 0,                       # 非负权重（不允许卖空）\n",
    "    w <= 0.05,                    # 单只股票权重≤5%（研报风险控制要求）\n",
    "]\n",
    "\n",
    "# 行业等权约束（若没有基准权重，强制各行业权重相等）\n",
    "for industry in selected_stocks['LEVEL1_NAME'].unique():\n",
    "    mask = (selected_stocks['LEVEL1_NAME'] == industry)\n",
    "    constraints.append(\n",
    "        cp.sum(w[mask]) == selected_stocks['行业权重'].unique()[0]  # 等权分配行业权重\n",
    "    )\n",
    "\n",
    "# 求解模型\n",
    "problem = cp.Problem(objective, constraints)\n",
    "problem.solve(solver=cp.SCS,verbose=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "ee50f988",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "最优组合权重分布（前5只）：\n",
      "           CODE LEVEL1_NAME            权重\n",
      "4053059  002916          电子 -1.857429e-05\n",
      "4613532  603297          电子 -1.805769e-05\n",
      "5492684  300793          电子 -1.857629e-05\n",
      "4543889  300724        机械设备  4.233836e-07\n",
      "5276915  300785          传媒  1.082234e-06\n",
      "\n",
      "行业权重分布：\n",
      "LEVEL1_NAME\n",
      "交通运输    0.04\n",
      "传媒      0.04\n",
      "公用事业    0.04\n",
      "农林牧渔    0.04\n",
      "医药生物    0.04\n",
      "国防军工    0.04\n",
      "基础化工    0.04\n",
      "家用电器    0.04\n",
      "建筑装饰    0.04\n",
      "房地产     0.04\n",
      "有色金属    0.04\n",
      "机械设备    0.04\n",
      "汽车      0.04\n",
      "电力设备    0.04\n",
      "电子      0.04\n",
      "社会服务    0.04\n",
      "纺织服饰    0.04\n",
      "综合      0.04\n",
      "计算机     0.04\n",
      "轻工制造    0.04\n",
      "通信      0.04\n",
      "采掘      0.04\n",
      "银行      0.04\n",
      "非银金融    0.04\n",
      "食品饮料    0.04\n",
      "Name: 权重, dtype: float64\n",
      "\n",
      "组合预期收益率：0.0960\n"
     ]
    }
   ],
   "source": [
    "# 最优权重\n",
    "selected_stocks['权重'] = w.value\n",
    "print(\"最优组合权重分布（前5只）：\")\n",
    "print(selected_stocks[['CODE', 'LEVEL1_NAME', '权重']].head())\n",
    "\n",
    "# 行业权重验证\n",
    "industry_allocation = selected_stocks.groupby('LEVEL1_NAME')['权重'].sum()\n",
    "print(\"\\n行业权重分布：\")\n",
    "print(industry_allocation)\n",
    "\n",
    "# 组合预期收益\n",
    "portfolio_return = selected_stocks['收益率'].values @ w.value\n",
    "print(f\"\\n组合预期收益率：{portfolio_return:.4f}\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "bc815e48",
   "metadata": {},
   "source": [
    "### **2.中性化因子**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 88,
   "id": "6e62ea17",
   "metadata": {},
   "outputs": [],
   "source": [
    "# 1. 筛选因子值最小的100只股票\n",
    "n_stocks = 100\n",
    "selected_stocks = data.sort_values('中性化因子_两步法', ascending=False).head(n_stocks)  # 升序排序，最小为1%分位\n",
    "n = n_stocks"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 89,
   "id": "1cd8f8a4",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "100"
      ]
     },
     "execution_count": 89,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(selected_stocks)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 90,
   "id": "d5bb3c60",
   "metadata": {},
   "outputs": [],
   "source": [
    "# 2.无行业基准权重，采用行业等权约束（替代方案）\n",
    "selected_stocks['行业权重'] = 1 / selected_stocks['LEVEL1_NAME'].nunique()  # 各行业等权分配"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 91,
   "id": "5ba9633c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "np.float64(0.09598682489890974)"
      ]
     },
     "execution_count": 91,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 3.求解模型\n",
    "\n",
    "# 定义变量\n",
    "w = cp.Variable(n)\n",
    "\n",
    "# 目标：最大化预测收益\n",
    "objective = cp.Maximize(selected_stocks['收益率'].values @ w)\n",
    "\n",
    "# 约束条件\n",
    "constraints = [\n",
    "    cp.sum(w) == 1,                # 权重和为1\n",
    "    w >= 0,                       # 非负权重（不允许卖空）\n",
    "    w <= 0.05,                    # 单只股票权重≤5%（研报风险控制要求）\n",
    "]\n",
    "\n",
    "# 行业等权约束（若没有基准权重，强制各行业权重相等）\n",
    "for industry in selected_stocks['LEVEL1_NAME'].unique():\n",
    "    mask = (selected_stocks['LEVEL1_NAME'] == industry)\n",
    "    constraints.append(\n",
    "        cp.sum(w[mask]) == selected_stocks['行业权重'].unique()[0]  # 等权分配行业权重\n",
    "    )\n",
    "\n",
    "# 求解模型\n",
    "problem = cp.Problem(objective, constraints)\n",
    "problem.solve(solver=cp.SCS,verbose=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 92,
   "id": "91d8ad31",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "最优组合权重分布（前5只）：\n",
      "           CODE LEVEL1_NAME            权重\n",
      "4053059  002916          电子 -1.212815e-05\n",
      "4613532  603297          电子 -1.143763e-05\n",
      "4543889  300724        机械设备  3.789957e-07\n",
      "5492684  300793          电子 -1.212949e-05\n",
      "5276915  300785          传媒 -2.186851e-07\n",
      "\n",
      "行业权重分布：\n",
      "LEVEL1_NAME\n",
      "交通运输    0.04\n",
      "传媒      0.04\n",
      "公用事业    0.04\n",
      "农林牧渔    0.04\n",
      "医药生物    0.04\n",
      "国防军工    0.04\n",
      "基础化工    0.04\n",
      "家用电器    0.04\n",
      "建筑装饰    0.04\n",
      "房地产     0.04\n",
      "有色金属    0.04\n",
      "机械设备    0.04\n",
      "汽车      0.04\n",
      "电力设备    0.04\n",
      "电子      0.04\n",
      "社会服务    0.04\n",
      "纺织服饰    0.04\n",
      "综合      0.04\n",
      "计算机     0.04\n",
      "轻工制造    0.04\n",
      "通信      0.04\n",
      "采掘      0.04\n",
      "银行      0.04\n",
      "非银金融    0.04\n",
      "食品饮料    0.04\n",
      "Name: 权重, dtype: float64\n",
      "\n",
      "组合预期收益率：0.0960\n"
     ]
    }
   ],
   "source": [
    "# 最优权重\n",
    "selected_stocks['权重'] = w.value\n",
    "print(\"最优组合权重分布（前5只）：\")\n",
    "print(selected_stocks[['CODE', 'LEVEL1_NAME', '权重']].head())\n",
    "\n",
    "# 行业权重验证\n",
    "industry_allocation = selected_stocks.groupby('LEVEL1_NAME')['权重'].sum()\n",
    "print(\"\\n行业权重分布：\")\n",
    "print(industry_allocation)\n",
    "\n",
    "# 组合预期收益\n",
    "portfolio_return = selected_stocks['收益率'].values @ w.value\n",
    "print(f\"\\n组合预期收益率：{portfolio_return:.4f}\")"
   ]
  }
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